random assignment outcome

Random Assignment in Psychology: Definition & Examples

Julia Simkus

Editor at Simply Psychology

BA (Hons) Psychology, Princeton University

Julia Simkus is a graduate of Princeton University with a Bachelor of Arts in Psychology. She is currently studying for a Master's Degree in Counseling for Mental Health and Wellness in September 2023. Julia's research has been published in peer reviewed journals.

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In psychology, random assignment refers to the practice of allocating participants to different experimental groups in a study in a completely unbiased way, ensuring each participant has an equal chance of being assigned to any group.

In experimental research, random assignment, or random placement, organizes participants from your sample into different groups using randomization.

Random assignment uses chance procedures to ensure that each participant has an equal opportunity of being assigned to either a control or experimental group.

The control group does not receive the treatment in question, whereas the experimental group does receive the treatment.

When using random assignment, neither the researcher nor the participant can choose the group to which the participant is assigned. This ensures that any differences between and within the groups are not systematic at the onset of the study.

In a study to test the success of a weight-loss program, investigators randomly assigned a pool of participants to one of two groups.

Group A participants participated in the weight-loss program for 10 weeks and took a class where they learned about the benefits of healthy eating and exercise.

Group B participants read a 200-page book that explains the benefits of weight loss. The investigator randomly assigned participants to one of the two groups.

The researchers found that those who participated in the program and took the class were more likely to lose weight than those in the other group that received only the book.

Importance

Random assignment ensures that each group in the experiment is identical before applying the independent variable.

In experiments , researchers will manipulate an independent variable to assess its effect on a dependent variable, while controlling for other variables. Random assignment increases the likelihood that the treatment groups are the same at the onset of a study.

Thus, any changes that result from the independent variable can be assumed to be a result of the treatment of interest. This is particularly important for eliminating sources of bias and strengthening the internal validity of an experiment.

Random assignment is the best method for inferring a causal relationship between a treatment and an outcome.

Random Selection vs. Random Assignment

Random selection (also called probability sampling or random sampling) is a way of randomly selecting members of a population to be included in your study.

On the other hand, random assignment is a way of sorting the sample participants into control and treatment groups.

Random selection ensures that everyone in the population has an equal chance of being selected for the study. Once the pool of participants has been chosen, experimenters use random assignment to assign participants into groups.

Random assignment is only used in between-subjects experimental designs, while random selection can be used in a variety of study designs.

Random Assignment vs Random Sampling

Random sampling refers to selecting participants from a population so that each individual has an equal chance of being chosen. This method enhances the representativeness of the sample.

Random assignment, on the other hand, is used in experimental designs once participants are selected. It involves allocating these participants to different experimental groups or conditions randomly.

This helps ensure that any differences in results across groups are due to manipulating the independent variable, not preexisting differences among participants.

When to Use Random Assignment

Random assignment is used in experiments with a between-groups or independent measures design.

In these research designs, researchers will manipulate an independent variable to assess its effect on a dependent variable, while controlling for other variables.

There is usually a control group and one or more experimental groups. Random assignment helps ensure that the groups are comparable at the onset of the study.

How to Use Random Assignment

There are a variety of ways to assign participants into study groups randomly. Here are a handful of popular methods:

Random Number Generator : Give each member of the sample a unique number; use a computer program to randomly generate a number from the list for each group.
Lottery : Give each member of the sample a unique number. Place all numbers in a hat or bucket and draw numbers at random for each group.
Flipping a Coin : Flip a coin for each participant to decide if they will be in the control group or experimental group (this method can only be used when you have just two groups)
Roll a Die : For each number on the list, roll a dice to decide which of the groups they will be in. For example, assume that rolling 1, 2, or 3 places them in a control group and rolling 3, 4, 5 lands them in an experimental group.

When is Random Assignment not used?

When it is not ethically permissible: Randomization is only ethical if the researcher has no evidence that one treatment is superior to the other or that one treatment might have harmful side effects.
When answering non-causal questions : If the researcher is just interested in predicting the probability of an event, the causal relationship between the variables is not important and observational designs would be more suitable than random assignment.
When studying the effect of variables that cannot be manipulated: Some risk factors cannot be manipulated and so it would not make any sense to study them in a randomized trial. For example, we cannot randomly assign participants into categories based on age, gender, or genetic factors.

Drawbacks of Random Assignment

While randomization assures an unbiased assignment of participants to groups, it does not guarantee the equality of these groups. There could still be extraneous variables that differ between groups or group differences that arise from chance. Additionally, there is still an element of luck with random assignments.

Thus, researchers can not produce perfectly equal groups for each specific study. Differences between the treatment group and control group might still exist, and the results of a randomized trial may sometimes be wrong, but this is absolutely okay.

Scientific evidence is a long and continuous process, and the groups will tend to be equal in the long run when data is aggregated in a meta-analysis.

Additionally, external validity (i.e., the extent to which the researcher can use the results of the study to generalize to the larger population) is compromised with random assignment.

Random assignment is challenging to implement outside of controlled laboratory conditions and might not represent what would happen in the real world at the population level.

Random assignment can also be more costly than simple observational studies, where an investigator is just observing events without intervening with the population.

Randomization also can be time-consuming and challenging, especially when participants refuse to receive the assigned treatment or do not adhere to recommendations.

What is the difference between random sampling and random assignment?

Random sampling refers to randomly selecting a sample of participants from a population. Random assignment refers to randomly assigning participants to treatment groups from the selected sample.

Does random assignment increase internal validity?

Yes, random assignment ensures that there are no systematic differences between the participants in each group, enhancing the study’s internal validity .

Does random assignment reduce sampling error?

Yes, with random assignment, participants have an equal chance of being assigned to either a control group or an experimental group, resulting in a sample that is, in theory, representative of the population.

Random assignment does not completely eliminate sampling error because a sample only approximates the population from which it is drawn. However, random sampling is a way to minimize sampling errors.

When is random assignment not possible?

Random assignment is not possible when the experimenters cannot control the treatment or independent variable.

For example, if you want to compare how men and women perform on a test, you cannot randomly assign subjects to these groups.

Participants are not randomly assigned to different groups in this study, but instead assigned based on their characteristics.

Does random assignment eliminate confounding variables?

Yes, random assignment eliminates the influence of any confounding variables on the treatment because it distributes them at random among the study groups. Randomization invalidates any relationship between a confounding variable and the treatment.

Why is random assignment of participants to treatment conditions in an experiment used?

Random assignment is used to ensure that all groups are comparable at the start of a study. This allows researchers to conclude that the outcomes of the study can be attributed to the intervention at hand and to rule out alternative explanations for study results.

Purpose and Limitations of Random Assignment

In an experimental study, random assignment is a process by which participants are assigned, with the same chance, to either a treatment or a control group. The goal is to assure an unbiased assignment of participants to treatment options.

Random assignment is considered the gold standard for achieving comparability across study groups, and therefore is the best method for inferring a causal relationship between a treatment (or intervention or risk factor) and an outcome.

Representation of random assignment in an experimental study

Random assignment of participants produces comparable groups regarding the participants’ initial characteristics, thereby any difference detected in the end between the treatment and the control group will be due to the effect of the treatment alone.

How does random assignment produce comparable groups?

1. random assignment prevents selection bias.

Randomization works by removing the researcher’s and the participant’s influence on the treatment allocation. So the allocation can no longer be biased since it is done at random, i.e. in a non-predictable way.

This is in contrast with the real world, where for example, the sickest people are more likely to receive the treatment.

2. Random assignment prevents confounding

A confounding variable is one that is associated with both the intervention and the outcome, and thus can affect the outcome in 2 ways:

Causal diagram representing how confounding works

Either directly:

Direct influence of confounding on the outcome

Or indirectly through the treatment:

Indirect influence of confounding on the outcome

This indirect relationship between the confounding variable and the outcome can cause the treatment to appear to have an influence on the outcome while in reality the treatment is just a mediator of that effect (as it happens to be on the causal pathway between the confounder and the outcome).

Random assignment eliminates the influence of the confounding variables on the treatment since it distributes them at random between the study groups, therefore, ruling out this alternative path or explanation of the outcome.

How random assignment protects from confounding

3. Random assignment also eliminates other threats to internal validity

By distributing all threats (known and unknown) at random between study groups, participants in both the treatment and the control group become equally subject to the effect of any threat to validity. Therefore, comparing the outcome between the 2 groups will bypass the effect of these threats and will only reflect the effect of the treatment on the outcome.

These threats include:

History: This is any event that co-occurs with the treatment and can affect the outcome.
Maturation: This is the effect of time on the study participants (e.g. participants becoming wiser, hungrier, or more stressed with time) which might influence the outcome.
Regression to the mean: This happens when the participants’ outcome score is exceptionally good on a pre-treatment measurement, so the post-treatment measurement scores will naturally regress toward the mean — in simple terms, regression happens since an exceptional performance is hard to maintain. This effect can bias the study since it represents an alternative explanation of the outcome.

Note that randomization does not prevent these effects from happening, it just allows us to control them by reducing their risk of being associated with the treatment.

What if random assignment produced unequal groups?

Question: What should you do if after randomly assigning participants, it turned out that the 2 groups still differ in participants’ characteristics? More precisely, what if randomization accidentally did not balance risk factors that can be alternative explanations between the 2 groups? (For example, if one group includes more male participants, or sicker, or older people than the other group).

Short answer: This is perfectly normal, since randomization only assures an unbiased assignment of participants to groups, i.e. it produces comparable groups, but it does not guarantee the equality of these groups.

A more complete answer: Randomization will not and cannot create 2 equal groups regarding each and every characteristic. This is because when dealing with randomization there is still an element of luck. If you want 2 perfectly equal groups, you better match them manually as is done in a matched pairs design (for more information see my article on matched pairs design ).

This is similar to throwing a die: If you throw it 10 times, the chance of getting a specific outcome will not be 1/6. But it will approach 1/6 if you repeat the experiment a very large number of times and calculate the average number of times the specific outcome turned up.

So randomization will not produce perfectly equal groups for each specific study, especially if the study has a small sample size. But do not forget that scientific evidence is a long and continuous process, and the groups will tend to be equal in the long run when a meta-analysis aggregates the results of a large number of randomized studies.

So for each individual study, differences between the treatment and control group will exist and will influence the study results. This means that the results of a randomized trial will sometimes be wrong, and this is absolutely okay.

BOTTOM LINE:

Although the results of a particular randomized study are unbiased, they will still be affected by a sampling error due to chance. But the real benefit of random assignment will be when data is aggregated in a meta-analysis.

Limitations of random assignment

Randomized designs can suffer from:

1. Ethical issues:

Randomization is ethical only if the researcher has no evidence that one treatment is superior to the other.

Also, it would be unethical to randomly assign participants to harmful exposures such as smoking or dangerous chemicals.

2. Low external validity:

With random assignment, external validity (i.e. the generalizability of the study results) is compromised because the results of a study that uses random assignment represent what would happen under “ideal” experimental conditions, which is in general very different from what happens at the population level.

In the real world, people who take the treatment might be very different from those who don’t – so the assignment of participants is not a random event, but rather under the influence of all sort of external factors.

External validity can be also jeopardized in cases where not all participants are eligible or willing to accept the terms of the study.

3. Higher cost of implementation:

An experimental design with random assignment is typically more expensive than observational studies where the investigator’s role is just to observe events without intervening.

Experimental designs also typically take a lot of time to implement, and therefore are less practical when a quick answer is needed.

4. Impracticality when answering non-causal questions:

A randomized trial is our best bet when the question is to find the causal effect of a treatment or a risk factor.

Sometimes however, the researcher is just interested in predicting the probability of an event or a disease given some risk factors. In this case, the causal relationship between these variables is not important, making observational designs more suitable for such problems.

5. Impracticality when studying the effect of variables that cannot be manipulated:

The usual objective of studying the effects of risk factors is to propose recommendations that involve changing the level of exposure to these factors.

However, some risk factors cannot be manipulated, and so it does not make any sense to study them in a randomized trial. For example it would be impossible to randomly assign participants to age categories, gender, or genetic factors.

6. Difficulty to control participants:

These difficulties include:

Participants refusing to receive the assigned treatment.
Participants not adhering to recommendations.
Differential loss to follow-up between those who receive the treatment and those who don’t.

All of these issues might occur in a randomized trial, but might not affect an observational study.

Shadish WR, Cook TD, Campbell DT. Experimental and Quasi-Experimental Designs for Generalized Causal Inference . 2nd edition. Cengage Learning; 2001.
Friedman LM, Furberg CD, DeMets DL, Reboussin DM, Granger CB. Fundamentals of Clinical Trials . 5th ed. 2015 edition. Springer; 2015.

The Definition of Random Assignment According to Psychology

Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."

Emily is a board-certified science editor who has worked with top digital publishing brands like Voices for Biodiversity, Study.com, GoodTherapy, Vox, and Verywell.

Materio / Getty Images

Random assignment refers to the use of chance procedures in psychology experiments to ensure that each participant has the same opportunity to be assigned to any given group in a study to eliminate any potential bias in the experiment at the outset. Participants are randomly assigned to different groups, such as the treatment group versus the control group. In clinical research, randomized clinical trials are known as the gold standard for meaningful results.

Simple random assignment techniques might involve tactics such as flipping a coin, drawing names out of a hat, rolling dice, or assigning random numbers to a list of participants. It is important to note that random assignment differs from random selection .

While random selection refers to how participants are randomly chosen from a target population as representatives of that population, random assignment refers to how those chosen participants are then assigned to experimental groups.

Random Assignment In Research

To determine if changes in one variable will cause changes in another variable, psychologists must perform an experiment. Random assignment is a critical part of the experimental design that helps ensure the reliability of the study outcomes.

Researchers often begin by forming a testable hypothesis predicting that one variable of interest will have some predictable impact on another variable.

The variable that the experimenters will manipulate in the experiment is known as the independent variable , while the variable that they will then measure for different outcomes is known as the dependent variable. While there are different ways to look at relationships between variables, an experiment is the best way to get a clear idea if there is a cause-and-effect relationship between two or more variables.

Once researchers have formulated a hypothesis, conducted background research, and chosen an experimental design, it is time to find participants for their experiment. How exactly do researchers decide who will be part of an experiment? As mentioned previously, this is often accomplished through something known as random selection.

Random Selection

In order to generalize the results of an experiment to a larger group, it is important to choose a sample that is representative of the qualities found in that population. For example, if the total population is 60% female and 40% male, then the sample should reflect those same percentages.

Choosing a representative sample is often accomplished by randomly picking people from the population to be participants in a study. Random selection means that everyone in the group stands an equal chance of being chosen to minimize any bias. Once a pool of participants has been selected, it is time to assign them to groups.

By randomly assigning the participants into groups, the experimenters can be fairly sure that each group will have the same characteristics before the independent variable is applied.

Participants might be randomly assigned to the control group , which does not receive the treatment in question. The control group may receive a placebo or receive the standard treatment. Participants may also be randomly assigned to the experimental group , which receives the treatment of interest. In larger studies, there can be multiple treatment groups for comparison.

There are simple methods of random assignment, like rolling the die. However, there are more complex techniques that involve random number generators to remove any human error.

There can also be random assignment to groups with pre-established rules or parameters. For example, if you want to have an equal number of men and women in each of your study groups, you might separate your sample into two groups (by sex) before randomly assigning each of those groups into the treatment group and control group.

Random assignment is essential because it increases the likelihood that the groups are the same at the outset. With all characteristics being equal between groups, other than the application of the independent variable, any differences found between group outcomes can be more confidently attributed to the effect of the intervention.

Example of Random Assignment

Imagine that a researcher is interested in learning whether or not drinking caffeinated beverages prior to an exam will improve test performance. After randomly selecting a pool of participants, each person is randomly assigned to either the control group or the experimental group.

The participants in the control group consume a placebo drink prior to the exam that does not contain any caffeine. Those in the experimental group, on the other hand, consume a caffeinated beverage before taking the test.

Participants in both groups then take the test, and the researcher compares the results to determine if the caffeinated beverage had any impact on test performance.

A Word From Verywell

Random assignment plays an important role in the psychology research process. Not only does this process help eliminate possible sources of bias, but it also makes it easier to generalize the results of a tested sample of participants to a larger population.

Random assignment helps ensure that members of each group in the experiment are the same, which means that the groups are also likely more representative of what is present in the larger population of interest. Through the use of this technique, psychology researchers are able to study complex phenomena and contribute to our understanding of the human mind and behavior.

Lin Y, Zhu M, Su Z. The pursuit of balance: An overview of covariate-adaptive randomization techniques in clinical trials . Contemp Clin Trials. 2015;45(Pt A):21-25. doi:10.1016/j.cct.2015.07.011

Sullivan L. Random assignment versus random selection . In: The SAGE Glossary of the Social and Behavioral Sciences. SAGE Publications, Inc.; 2009. doi:10.4135/9781412972024.n2108

Alferes VR. Methods of Randomization in Experimental Design . SAGE Publications, Inc.; 2012. doi:10.4135/9781452270012

Nestor PG, Schutt RK. Research Methods in Psychology: Investigating Human Behavior. (2nd Ed.). SAGE Publications, Inc.; 2015.

By Kendra Cherry, MSEd Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."

All Subjects

Experimental Design

Study guides for every class, that actually explain what's on your next test, random assignment, from class:.

Random assignment is a technique used in experimental research to ensure that participants are allocated to different groups or conditions in a way that is not influenced by any biases or pre-existing differences. This process helps to create equivalent groups, enhancing the credibility of the experiment's conclusions by minimizing confounding variables.

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5 Must Know Facts For Your Next Test

Random assignment helps eliminate selection bias, ensuring that differences between groups are due to the experimental treatment rather than other variables.
This technique is crucial for internal validity, as it strengthens causal inferences by demonstrating that changes in outcomes can be attributed to the manipulated variables.
It allows researchers to generalize their findings to a larger population since it creates groups that are statistically equivalent on all relevant characteristics.
Random assignment can be achieved through methods like flipping a coin, using random number generators, or drawing lots to assign participants to groups.
It's essential for designing both between-subjects and within-subjects experiments, influencing how treatments are administered and compared.

Review Questions

Random assignment enhances internal validity by ensuring that each participant has an equal chance of being placed in any experimental group. This process reduces the likelihood of pre-existing differences between groups affecting the outcomes. By balancing out participant characteristics across conditions, researchers can confidently attribute observed effects to the treatment rather than other variables.
In between-subjects designs, random assignment helps create equivalent groups by randomly allocating different participants to separate conditions. In within-subjects designs, although all participants experience all conditions, random assignment can still be applied to determine the order in which they encounter those conditions. This approach minimizes order effects and ensures that any differences observed are due to the treatments themselves.
Stratified random sampling involves dividing a population into subgroups and then randomly selecting from these groups to ensure representation across key characteristics. When combined with random assignment in an experiment, researchers first use stratified sampling to form a diverse participant pool and then employ random assignment to allocate these individuals into experimental groups. This integration ensures that the groups are both representative of the overall population and balanced in terms of critical variables, enhancing both internal and external validity of the findings.

Related terms

A group of participants that does not receive the experimental treatment, allowing researchers to compare outcomes against those who do receive it.

A method used to select participants for a study where each individual has an equal chance of being chosen, aiming to ensure the sample represents the broader population.

A technique where participants and/or researchers are kept unaware of which group participants belong to, reducing bias in the treatment administration and outcome assessment.

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Random Assignment

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First Online: 01 January 2020
pp 4260–4262
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Sven Hilbert 3 , 4 , 5

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Random assignment defines the assignment of participants of a study to their respective group strictly by chance.

Introduction

Statistical inference is based on the theory of probability, and effects investigated in psychological studies are defined by measures that are treated as random variables. The inference about the probability of a given result with regard to an assumed population and the popular term “significance” are only meaningful and without bias if the measure of interest is really a random variable. To achieve the creation of a random variable in form of a measure derived from a sample of participants, these participants have to be randomly drawn. In an experimental study involving different groups of participants, these participants have to additionally be randomly assigned to one of the groups.

Why Is Random Assignment Crucial for Statistical Inference?

Many psychological investigations, such as clinical treatment studies or neuropsychological training...

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Gigerenzer, G., Swijtink, Z., Porter, T., Daston, L., Beatty, J., & Kruger, L. (1989). The empire of chance: How probability changed science and everyday-life . Cambridge: New York.

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Department of Psychology, Psychological Methods and Assessment, Münich, Germany

Sven Hilbert

Faculty of Psychology, Educational Science, and Sport Science, University of Regensburg, Regensburg, Germany

Psychological Methods and Assessment, LMU Munich, Munich, Germany

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Correspondence to Sven Hilbert .

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Hilbert, S. (2020). Random Assignment. In: Zeigler-Hill, V., Shackelford, T.K. (eds) Encyclopedia of Personality and Individual Differences. Springer, Cham. https://doi.org/10.1007/978-3-319-24612-3_1343

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Applied Causal Analysis (with R)

4.23 independence assumption & random assignment.

= a statistical solution (Holland 1986 , 948f)
Units randomly assigned to treatment/control have identical distributions of covariates/potential outcomes in both groups ( (infinite) long run! ) 25
Random assignment induces independence between treatment status and potential outcomes
Contrast a randomized experiment here in the class (e.g., N = 4) with a bigger sample (e.g., N = 1000).
Compare average outcome among treatment units with average outcome among control units

Holland, Paul W. 1986. “Statistics and Causal Inference.” J. Am. Stat. Assoc. 81 (396): 945–60.

“When units are assigned at random either to cause t or to cause c, certain physical randomization processes are carried out so that the determination of which cause (t or c) u is exposed to is regarded as statistically independent of all other variables, including Y t and Y c . This means that if the physical randomization is carried out correctly, then it is plausible that S [= treatment D] is independent of Y, and Y, and all other variables over U. This is the independence assumption” (Holland 1986 , 948) . ↩

Random Assignment in Psychology (Intro for Students)

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Random assignment is a research procedure used to randomly assign participants to different experimental conditions (or ‘groups’). This introduces the element of chance, ensuring that each participant has an equal likelihood of being placed in any condition group for the study.

It is absolutely essential that the treatment condition and the control condition are the same in all ways except for the variable being manipulated.

Using random assignment to place participants in different conditions helps to achieve this.

It ensures that those conditions are the same in regards to all potential confounding variables and extraneous factors .

Why Researchers Use Random Assignment

Researchers use random assignment to control for confounds in research.

Confounds refer to unwanted and often unaccounted-for variables that might affect the outcome of a study. These confounding variables can skew the results, rendering the experiment unreliable.

For example, below is a study with two groups. Note how there are more ‘red’ individuals in the first group than the second:

a representation of a treatment condition showing 12 red people in the cohort

There is likely a confounding variable in this experiment explaining why more red people ended up in the treatment condition and less in the control condition. The red people might have self-selected, for example, leading to a skew of them in one group over the other.

Ideally, we’d want a more even distribution, like below:

a representation of a treatment condition showing 4 red people in the cohort

To achieve better balance in our two conditions, we use randomized sampling.

Fact File: Experiments 101

Random assignment is used in the type of research called the experiment.

An experiment involves manipulating the level of one variable and examining how it affects another variable. These are the independent and dependent variables :

Independent Variable: The variable manipulated is called the independent variable (IV)
Dependent Variable: The variable that it is expected to affect is called the dependent variable (DV).

The most basic form of the experiment involves two conditions: the treatment and the control .

The Treatment Condition: The treatment condition involves the participants being exposed to the IV.
The Control Condition: The control condition involves the absence of the IV. Therefore, the IV has two levels: zero and some quantity.

Researchers utilize random assignment to determine which participants go into which conditions.

Methods of Random Assignment

There are several procedures that researchers can use to randomly assign participants to different conditions.

1. Random number generator

There are several websites that offer computer-generated random numbers. Simply indicate how many conditions are in the experiment and then click. If there are 4 conditions, the program will randomly generate a number between 1 and 4 each time it is clicked.

2. Flipping a coin

If there are two conditions in an experiment, then the simplest way to implement random assignment is to flip a coin for each participant. Heads means being assigned to the treatment and tails means being assigned to the control (or vice versa).

3. Rolling a die

Rolling a single die is another way to randomly assign participants. If the experiment has three conditions, then numbers 1 and 2 mean being assigned to the control; numbers 3 and 4 mean treatment condition one; and numbers 5 and 6 mean treatment condition two.

4. Condition names in a hat

In some studies, the researcher will write the name of the treatment condition(s) or control on slips of paper and place them in a hat. If there are 4 conditions and 1 control, then there are 5 slips of paper.

The researcher closes their eyes and selects one slip for each participant. That person is then assigned to one of the conditions in the study and that slip of paper is placed back in the hat. Repeat as necessary.

There are other ways of trying to ensure that the groups of participants are equal in all ways with the exception of the IV. However, random assignment is the most often used because it is so effective at reducing confounds.

Read About More Methods and Examples of Random Assignment Here

Potential Confounding Effects

Random assignment is all about minimizing confounding effects.

Here are six types of confounds that can be controlled for using random assignment:

Individual Differences: Participants in a study will naturally vary in terms of personality, intelligence, mood, prior knowledge, and many other characteristics. If one group happens to have more people with a particular characteristic, this could affect the results. Random assignment ensures that these individual differences are spread out equally among the experimental groups, making it less likely that they will unduly influence the outcome.
Temporal or Time-Related Confounds: Events or situations that occur at a particular time can influence the outcome of an experiment. For example, a participant might be tested after a stressful event, while another might be tested after a relaxing weekend. Random assignment ensures that such effects are equally distributed among groups, thus controlling for their potential influence.
Order Effects: If participants are exposed to multiple treatments or tests, the order in which they experience them can influence their responses. Randomly assigning the order of treatments for different participants helps control for this.
Location or Environmental Confounds: The environment in which the study is conducted can influence the results. One group might be tested in a noisy room, while another might be in a quiet room. Randomly assigning participants to different locations can control for these effects.
Instrumentation Confounds: These occur when there are variations in the calibration or functioning of measurement instruments across conditions. If one group’s responses are being measured using a slightly different tool or scale, it can introduce a confound. Random assignment can ensure that any such potential inconsistencies in instrumentation are equally distributed among groups.
Experimenter Effects: Sometimes, the behavior or expectations of the person administering the experiment can unintentionally influence the participants’ behavior or responses. For instance, if an experimenter believes one treatment is superior, they might unconsciously communicate this belief to participants. Randomly assigning experimenters or using a double-blind procedure (where neither the participant nor the experimenter knows the treatment being given) can help control for this.

Random assignment helps balance out these and other potential confounds across groups, ensuring that any observed differences are more likely due to the manipulated independent variable rather than some extraneous factor.

Limitations of the Random Assignment Procedure

Although random assignment is extremely effective at eliminating the presence of participant-related confounds, there are several scenarios in which it cannot be used.

Ethics: The most obvious scenario is when it would be unethical. For example, if wanting to investigate the effects of emotional abuse on children, it would be unethical to randomly assign children to either received abuse or not. Even if a researcher were to propose such a study, it would not receive approval from the Institutional Review Board (IRB) which oversees research by university faculty.
Practicality: Other scenarios involve matters of practicality. For example, randomly assigning people to specific types of diet over a 10-year period would be interesting, but it would be highly unlikely that participants would be diligent enough to make the study valid. This is why examining these types of subjects has to be carried out through observational studies . The data is correlational, which is informative, but falls short of the scientist’s ultimate goal of identifying causality.
Small Sample Size: The smaller the sample size being assigned to conditions, the more likely it is that the two groups will be unequal. For example, if you flip a coin many times in a row then you will notice that sometimes there will be a string of heads or tails that come up consecutively. This means that one condition may have a build-up of participants that share the same characteristics. However, if you continue flipping the coin, over the long-term, there will be a balance of heads and tails. Unfortunately, how large a sample size is necessary has been the subject of considerable debate (Bloom, 2006; Shadish et al., 2002).

“It is well known that larger sample sizes reduce the probability that random assignment will result in conditions that are unequal” (Goldberg, 2019, p. 2).

Applications of Random Assignment

The importance of random assignment has been recognized in a wide range of scientific and applied disciplines (Bloom, 2006).

Random assignment began as a tool in agricultural research by Fisher (1925, 1935). After WWII, it became extensively used in medical research to test the effectiveness of new treatments and pharmaceuticals (Marks, 1997).

Today it is widely used in industrial engineering (Box, Hunter, and Hunter, 2005), educational research (Lindquist, 1953; Ong-Dean et al., 2011)), psychology (Myers, 1972), and social policy studies (Boruch, 1998; Orr, 1999).

One of the biggest obstacles to the validity of an experiment is the confound. If the group of participants in the treatment condition are substantially different from the group in the control condition, then it is impossible to determine if the IV has an affect or if the confound has an effect.

Thankfully, random assignment is highly effective at eliminating confounds that are known and unknown. Because each participant has an equal chance of being placed in each condition, they are equally distributed.

There are several ways of implementing random assignment, including flipping a coin or using a random number generator.

Random assignment has become an essential procedure in research in a wide range of subjects such as psychology, education, and social policy.

Alferes, V. R. (2012). Methods of randomization in experimental design . Sage Publications.

Bloom, H. S. (2008). The core analytics of randomized experiments for social research. The SAGE Handbook of Social Research Methods , 115-133.

Boruch, R. F. (1998). Randomized controlled experiments for evaluation and planning. Handbook of applied social research methods , 161-191.

Box, G. E., Hunter, W. G., & Hunter, J. S. (2005). Design of experiments: Statistics for Experimenters: Design, Innovation and Discovery.

Dehue, T. (1997). Deception, efficiency, and random groups: Psychology and the gradual origination of the random group design. Isis , 88 (4), 653-673.

Fisher, R.A. (1925). Statistical methods for research workers (11th ed. rev.). Oliver and Boyd: Edinburgh.

Fisher, R. A. (1935). The Design of Experiments. Edinburgh: Oliver and Boyd.

Goldberg, M. H. (2019). How often does random assignment fail? Estimates and recommendations. Journal of Environmental Psychology , 66 , 101351.

Jamison, J. C. (2019). The entry of randomized assignment into the social sciences. Journal of Causal Inference , 7 (1), 20170025.

Lindquist, E. F. (1953). Design and analysis of experiments in psychology and education . Boston: Houghton Mifflin Company.

Marks, H. M. (1997). The progress of experiment: Science and therapeutic reform in the United States, 1900-1990 . Cambridge University Press.

Myers, J. L. (1972). Fundamentals of experimental design (2nd ed.). Allyn & Bacon.

Ong-Dean, C., Huie Hofstetter, C., & Strick, B. R. (2011). Challenges and dilemmas in implementing random assignment in educational research. American Journal of Evaluation , 32 (1), 29-49.

Orr, L. L. (1999). Social experiments: Evaluating public programs with experimental methods . Sage.

Shadish, W. R., Cook, T. D., & Campbell, D. T. (2002). Quasi-experiments: interrupted time-series designs. Experimental and quasi-experimental designs for generalized causal inference , 171-205.

Stigler, S. M. (1992). A historical view of statistical concepts in psychology and educational research. American Journal of Education , 101 (1), 60-70.

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Completing a research or thesis paper is more work than most students imagine. For instance, you must conduct experiments before coming up with conclusions. Random assignment, a key methodology in academic research, ensures every participant has an equal chance of being placed in any group within an experiment. In experimental studies, the random assignment of participants is a vital element, which this article will discuss.

Inhaltsverzeichnis

1 Random Assignment – In a Nutshell
2 Definition: Random assignment
3 Importance of random assignment
4 Random assignment vs. random sampling
5 How to use random assignment
6 When random assignment is not used

Random Assignment – In a Nutshell

Random assignment is where you randomly place research participants into specific groups.
This method eliminates bias in the results by ensuring that all participants have an equal chance of getting into either group.
Random assignment is usually used in independent measures or between-group experiment designs.

Definition: Random assignment

Pearson Correlation is a descriptive statistical procedure that describes the measure of linear dependence between two variables. It entails a sample, control group , experimental design , and randomized design. In this statistical procedure, random assignment is used. Random assignment is the random placement of participants into different groups in experimental research.

Importance of random assignment

Random assessment is essential for strengthening the internal validity of experimental research. Internal validity helps make a casual relationship’s conclusions reliable and trustworthy.

In experimental research, researchers isolate independent variables and manipulate them as they assess the impact while managing other variables. To achieve this, an independent variable for diverse member groups is vital. This experimental design is called an independent or between-group design.

Example: Different levels of independent variables

In a medical study, you can research the impact of nutrient supplements on the immune (nutrient supplements = independent variable, immune = dependent variable)

Three independent participant levels are applicable here:

Control group (given 0 dosages of iron supplements)
The experimental group (low dosage)
The second experimental group (high dosage)

This assignment technique in experiments ensures no bias in the treatment sets at the beginning of the trials. Therefore, if you do not use this technique, you won’t be able to exclude any alternate clarifications for your findings.

In the research experiment above, you can recruit participants randomly by handing out flyers at public spaces like gyms, cafés, and community centers. Then:

Place the group from cafés in the control group
Community center group in the low prescription trial group
Gym group in the high-prescription group

Even with random participant assignment, other extraneous variables may still create bias in experiment results. However, these variations are usually low, hence should not hinder your research. Therefore, using random placement in experiments is highly necessary, especially where it is ethically required or makes sense for your research subject.

Random assignment vs. random sampling

Simple random sampling is a method of choosing the participants for a study. On the other hand, the random assignment involves sorting the participants selected through random sampling. Another difference between random sampling and random assignment is that the former is used in several types of studies, while the latter is only applied in between-subject experimental designs.

Your study researches the impact of technology on productivity in a specific company.

In such a case, you have contact with the entire staff. So, you can assign each employee a quantity and apply a random number generator to pick a specific sample.

For instance, from 500 employees, you can pick 200. So, the full sample is 200.

Random sampling enhances external validity, as it guarantees that the study sample is unbiased, and that an entire population is represented. This way, you can conclude that the results of your studies can be accredited to the autonomous variable.

After determining the full sample, you can break it down into two groups using random assignment. In this case, the groups are:

The control group (does get access to technology)
The experimental group (gets access to technology)

Using random assignment assures you that any differences in the productivity results for each group are not biased and will help the company make a decision.

How to use random assignment

Firstly, give each participant a unique number as an identifier. Then, use a specific tool to simplify assigning the participants to the sample groups. Some tools you can use are:

Random member assignment is a prevailing technique for placing participants in specific groups because each person has a fair opportunity of being put in either group.

Random assignment in block experimental designs

In complex experimental designs , you must group your participants into blocks before using the random assignment technique.

You can create participant blocks depending on demographic variables, working hours, or scores. However, the blocks imply that you will require a bigger sample to attain high statistical power.

After grouping the participants in blocks, you can use random assignments inside each block to allocate the members to a specific treatment condition. Doing this will help you examine if quality impacts the result of the treatment.

Depending on their unique characteristics, you can also use blocking in experimental matched designs before matching the participants in each block. Then, you can randomly allot each partaker to one of the treatments in the research and examine the results.

When random assignment is not used

As powerful a tool as it is, random assignment does not apply in all situations. Like the following:

Comparing different groups

When the purpose of your study is to assess the differences between the participants, random member assignment may not work.

If you want to compare teens and the elderly with and without specific health conditions, you must ensure that the participants have specific characteristics. Therefore, you cannot pick them randomly.

In such a study, the medical condition (quality of interest) is the independent variable, and the participants are grouped based on their ages (different levels). Also, all partakers are tried similarly to ensure they have the medical condition, and their outcomes are tested per group level.

No ethical justifiability

Another situation where you cannot use random assignment is if it is ethically not permitted.

If your study involves unhealthy or dangerous behaviors or subjects, such as drug use. Instead of assigning random partakers to sets, you can conduct quasi-experimental research.

When using a quasi-experimental design , you examine the conclusions of pre-existing groups you have no control over, such as existing drug users. While you cannot randomly assign them to groups, you can use variables like their age, years of drug use, or socioeconomic status to group the participants.

What is the definition of random assignment?

It is an experimental research technique that involves randomly placing participants from your samples into different groups. It ensures that every sample member has the same opportunity of being in whichever group (control or experimental group).

When is random assignment applicable?

You can use this placement technique in experiments featuring an independent measures design. It helps ensure that all your sample groups are comparable.

What is the importance of random assignment?

It can help you enhance your study’s validity . This technique also helps ensure that every sample has an equal opportunity of being assigned to a control or trial group.

When should you NOT use random assignment

You should not use this technique if your study focuses on group comparisons or if it is not legally ethical.

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Random Assignment in Experiments | Introduction & Examples

Random Assignment in Experiments | Introduction & Examples

Published on 6 May 2022 by Pritha Bhandari . Revised on 13 February 2023.

In experimental research, random assignment is a way of placing participants from your sample into different treatment groups using randomisation.

With simple random assignment, every member of the sample has a known or equal chance of being placed in a control group or an experimental group. Studies that use simple random assignment are also called completely randomised designs .

Random assignment is a key part of experimental design . It helps you ensure that all groups are comparable at the start of a study: any differences between them are due to random factors.

Why does random assignment matter, random sampling vs random assignment, how do you use random assignment, when is random assignment not used, frequently asked questions about random assignment.

Random assignment is an important part of control in experimental research, because it helps strengthen the internal validity of an experiment.

In experiments, researchers manipulate an independent variable to assess its effect on a dependent variable, while controlling for other variables. To do so, they often use different levels of an independent variable for different groups of participants.

This is called a between-groups or independent measures design.

You use three groups of participants that are each given a different level of the independent variable:

A control group that’s given a placebo (no dosage)
An experimental group that’s given a low dosage
A second experimental group that’s given a high dosage

Random assignment to helps you make sure that the treatment groups don’t differ in systematic or biased ways at the start of the experiment.

If you don’t use random assignment, you may not be able to rule out alternative explanations for your results.

Participants recruited from pubs are placed in the control group
Participants recruited from local community centres are placed in the low-dosage experimental group
Participants recruited from gyms are placed in the high-dosage group

With this type of assignment, it’s hard to tell whether the participant characteristics are the same across all groups at the start of the study. Gym users may tend to engage in more healthy behaviours than people who frequent pubs or community centres, and this would introduce a healthy user bias in your study.

Although random assignment helps even out baseline differences between groups, it doesn’t always make them completely equivalent. There may still be extraneous variables that differ between groups, and there will always be some group differences that arise from chance.

Most of the time, the random variation between groups is low, and, therefore, it’s acceptable for further analysis. This is especially true when you have a large sample. In general, you should always use random assignment in experiments when it is ethically possible and makes sense for your study topic.

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Random sampling and random assignment are both important concepts in research, but it’s important to understand the difference between them.

Random sampling (also called probability sampling or random selection) is a way of selecting members of a population to be included in your study. In contrast, random assignment is a way of sorting the sample participants into control and experimental groups.

While random sampling is used in many types of studies, random assignment is only used in between-subjects experimental designs.

Some studies use both random sampling and random assignment, while others use only one or the other.

Random sampling enhances the external validity or generalisability of your results, because it helps to ensure that your sample is unbiased and representative of the whole population. This allows you to make stronger statistical inferences .

You use a simple random sample to collect data. Because you have access to the whole population (all employees), you can assign all 8,000 employees a number and use a random number generator to select 300 employees. These 300 employees are your full sample.

Random assignment enhances the internal validity of the study, because it ensures that there are no systematic differences between the participants in each group. This helps you conclude that the outcomes can be attributed to the independent variable .

A control group that receives no intervention
An experimental group that has a remote team-building intervention every week for a month

You use random assignment to place participants into the control or experimental group. To do so, you take your list of participants and assign each participant a number. Again, you use a random number generator to place each participant in one of the two groups.

To use simple random assignment, you start by giving every member of the sample a unique number. Then, you can use computer programs or manual methods to randomly assign each participant to a group.

Random number generator: Use a computer program to generate random numbers from the list for each group.
Lottery method: Place all numbers individually into a hat or a bucket, and draw numbers at random for each group.
Flip a coin: When you only have two groups, for each number on the list, flip a coin to decide if they’ll be in the control or the experimental group.
Use a dice: When you have three groups, for each number on the list, roll a die to decide which of the groups they will be in. For example, assume that rolling 1 or 2 lands them in a control group; 3 or 4 in an experimental group; and 5 or 6 in a second control or experimental group.

This type of random assignment is the most powerful method of placing participants in conditions, because each individual has an equal chance of being placed in any one of your treatment groups.

Random assignment in block designs

In more complicated experimental designs, random assignment is only used after participants are grouped into blocks based on some characteristic (e.g., test score or demographic variable). These groupings mean that you need a larger sample to achieve high statistical power .

For example, a randomised block design involves placing participants into blocks based on a shared characteristic (e.g., college students vs graduates), and then using random assignment within each block to assign participants to every treatment condition. This helps you assess whether the characteristic affects the outcomes of your treatment.

In an experimental matched design , you use blocking and then match up individual participants from each block based on specific characteristics. Within each matched pair or group, you randomly assign each participant to one of the conditions in the experiment and compare their outcomes.

Sometimes, it’s not relevant or ethical to use simple random assignment, so groups are assigned in a different way.

When comparing different groups

Sometimes, differences between participants are the main focus of a study, for example, when comparing children and adults or people with and without health conditions. Participants are not randomly assigned to different groups, but instead assigned based on their characteristics.

In this type of study, the characteristic of interest (e.g., gender) is an independent variable, and the groups differ based on the different levels (e.g., men, women). All participants are tested the same way, and then their group-level outcomes are compared.

When it’s not ethically permissible

When studying unhealthy or dangerous behaviours, it’s not possible to use random assignment. For example, if you’re studying heavy drinkers and social drinkers, it’s unethical to randomly assign participants to one of the two groups and ask them to drink large amounts of alcohol for your experiment.

When you can’t assign participants to groups, you can also conduct a quasi-experimental study . In a quasi-experiment, you study the outcomes of pre-existing groups who receive treatments that you may not have any control over (e.g., heavy drinkers and social drinkers).

These groups aren’t randomly assigned, but may be considered comparable when some other variables (e.g., age or socioeconomic status) are controlled for.

In experimental research, random assignment is a way of placing participants from your sample into different groups using randomisation. With this method, every member of the sample has a known or equal chance of being placed in a control group or an experimental group.

Random selection, or random sampling , is a way of selecting members of a population for your study’s sample.

In contrast, random assignment is a way of sorting the sample into control and experimental groups.

Random sampling enhances the external validity or generalisability of your results, while random assignment improves the internal validity of your study.

Random assignment is used in experiments with a between-groups or independent measures design. In this research design, there’s usually a control group and one or more experimental groups. Random assignment helps ensure that the groups are comparable.

In general, you should always use random assignment in this type of experimental design when it is ethically possible and makes sense for your study topic.

To implement random assignment , assign a unique number to every member of your study’s sample .

Then, you can use a random number generator or a lottery method to randomly assign each number to a control or experimental group. You can also do so manually, by flipping a coin or rolling a die to randomly assign participants to groups.

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Published: 13 November 2024

Ultrasonic dissection versus electrocautery dissection in laparoscopic cholecystectomy for acute cholecystitis: a randomized controlled trial (SONOCHOL-trial)

My Blohm 1 , 2 , 3 ,
Gabriel Sandblom 1 ,
Lars Enochsson 4 , 5 ,
Yücel Cengiz 4 ,
Haytham Bayadsi 4 ,
Joakim Hennings 4 ,
Angelica Diaz Pannes 6 ,
Erik Stenberg 7 ,
Kerstin Bewö 8 &
Johanna Österberg 1 , 2 , 3

World Journal of Emergency Surgery volume 19 , Article number: 34 ( 2024 ) Cite this article

Metrics details

Laparoscopic cholecystectomy with ultrasonic dissection presents a compelling alternative to conventional electrocautery. The evidence for elective cholecystectomy supports the adoption of ultrasonic dissection, citing advantages such as reduced operating time, diminished bleeding, shorter hospital stays and decreased postoperative pain and nausea. However, the efficacy of this procedure in emergency surgery and patients diagnosed with acute cholecystitis remains uncertain. The aim of this study was to compare outcomes of electrocautery and ultrasonic dissection in patients with acute cholecystitis.

A randomized, parallel, double-blinded, multicentre controlled trial was conducted across eight Swedish hospitals. Eligible participants were individuals aged ≥ 18 years with acute cholecystitis lasting ≤ 7 days. Laparoscopic cholecystectomy was performed in the emergency setting as soon as local circumstances permitted. Random allocation to electrocautery or ultrasonic dissection was performed in a 1:1 ratio. The primary endpoint was the total complication rate, analysed using an intention-to-treat approach. The primary outcome was analysed using logistic generalized estimated equations. Patients, postoperative caregivers, and follow-up personnel were blinded to group assignment.

From September 2019 to March 2023, 300 patients were enrolled and randomly assigned to electrocautery dissection (n = 148) and ultrasonic dissection (n = 152). No significant difference in complication rate was observed between the groups (risk difference [RD] 1.6%, 95% confidence interval [CI], − 7.2% to 10.4%, P = 0.720). No significant disparities in operating time, conversion rate, hospital stay or readmission rates between the groups were noted. Haemostatic agents were more frequently used in electrocautery dissection (RD 10.6%, 95% CI, 1.3% to 19.8%, P = 0.025).

Conclusions

Ultrasonic dissection and electrocautery dissection demonstrate comparable risks for complications in emergency surgery for patients with acute cholecystitis. Ultrasonic dissection is a viable alternative to electrocautery dissection or can be used as a complementary method in laparoscopic cholecystectomy for acute cholecystitis.

Trial registration

The trial was registered prior to conducting the research on http://clinical.trials.gov , NCT03014817.

Laparoscopic cholecystectomy by ultrasonic dissection is an established alternative to traditional monopolar electrocautery dissection. Previous research on elective cholecystectomy supports the use of ultrasonic dissection because of its numerous benefits, including reduced operating time, diminished bleeding, fewer gallbladder perforations, shorter hospitalization and decreased postoperative pain and nausea [ 1 , 2 , 3 , 4 , 5 , 6 , 7 , 8 , 9 , 10 , 11 ]. Comparable outcomes have also been demonstrated [ 12 , 13 ]. Despite these advantages, counterarguments to widespread adoption include increased instrumental costs and challenges in instrument handling during the learning curve. Therefore, the preferred instrument for most surgeons continues to be monopolar electrocautery.

The unique features of the ultrasonic instrument —allowing for both cutting and coagulation for bleeding control, as well as tissue sealing and vaporization capacities —offer theoretical advantages in emergent surgical settings involving acute cholecystitis, where hyper-vascularized, oedematous tissue and omental adhesions are common [ 14 ]. These capabilities may provide notable benefits during acute cholecystectomies. However, evidence supporting its use in emergency surgery is sparce, with only a few small studies published on its application in acute cholecystitis. For instance, a randomized single-centre study of 42 patients with acute cholecystitis reported fewer conversions and reduced blood loss using ultrasonic dissection [ 15 ]. Additionally, subgroup analyses of intraoperatively diagnosed acute cholecystitis in elective studies have demonstrated shorter operating times [ 2 ]. However, whether ultrasonic dissection decreases intra- and postoperative complications remains uncertain. The complication rates in emergent versus elective cholecystectomies are nearly twice as high, highlighting the need for improved surgical safety in this group [ 16 ].

This study aimed to compare intra- and postoperative complications and outcomes in patients undergoing laparoscopic cholecystectomy for acute cholecystitis using ultrasonic dissection or electrocautery dissection. It was conducted as a phase 3 trial following a phase 2b pilot study on the learning curve for ultrasonic fundus-first dissection in elective cholecystectomy [ 17 , 18 ].

Study design

From 2019 to 2023, a randomized, parallel, multicentre, double-blinded, controlled trial was conducted across eight Swedish hospitals. The study was approved by the Regional Research Ethics Committee in Stockholm, Sweden (2016/1434–31/4, 2018/2587–32). The study report was structured under the CONSORT reporting guidelines [ 19 ].

Participants

Eligible participants were patients ≥ 18 years old, diagnosed with acute cholecystitis according to the Tokyo guideline criteria [ 20 ] with a symptom duration of ≤ 7 days. Exclusion criteria were (1) American Society of Anaesthesiologists (ASA) physical status classification score of ≥ 4, (2) severe cholecystitis (Grade III as per the Tokyo guidelines) [ 20 ], (3) previous major upper abdominal surgery, (4) preoperative drainage of the gallbladder, (5) other acute or chronic abdominal diseases (e.g., pancreatitis, cirrhosis or hepatitis) with elevated liver enzymes, (6) pregnancy or (7) the inability to understand written instructions in Swedish. Patients were recruited before surgery. Oral and written informed consent was retrieved from all participants.

All participating surgeons were specialists or last year fellows in general surgery with previous experience with electrocautery and ultrasonic dissection. Experience from ultrasonic dissection was verified by inclusion in the pilot study [ 18 ], with surgeons performing ≥ 15 operations with the ultrasonic device or by video assessment.

The duration of symptoms in days, previous biliary colic, and the severity grade of cholecystitis [ 20 ], were registered upon inclusion. The participants were given a diary to evaluate the level of pain and nausea before and after the operation. They were also instructed to track their intake of pain medications and complete quality-of-life questionnaires (EQ-5D-5L) [ 21 ].

The operation was performed as early as the local circumstances allowed. The operating surgeon completed an electronic case report form (eCRF). All patients were registered in the Swedish Registry of Gallstone Surgery and Endoscopic Retrograde Cholangiopancreatography (GallRiks) [ 22 ]. It has a national coverage of 94.5% with a 97% follow-up frequency [ 16 ] and data have consistently shown high accuracy in reporting serious adverse events [ 23 ]. Patients were postoperatively treated according to local routines. Antibiotics were not routinely administered but were prescribed by the surgeon when indicated. Thrombosis prophylaxis was given to patients with risk factors for thrombotic events or extended operating times. Laboratory tests of red and white blood cell count, C-reactive protein and liver function tests were registered preoperatively, 24 h after surgery or earlier if the patient was discharged. Patients continued to fill out the diary for 7 days. Intra- and postoperative complications were retrieved from the eCRF and GallRiks, including a 30-day follow-up based on medical records. A telephone follow-up was registered by a research nurse at the principal study site 30 days after surgery. The eCRFs were periodically evaluated to identify any incorrect registrations, and the principal investigator was accessible to address inquiries throughout the study.

Surgical intervention

Anaesthesia was conducted according to local routines. A standardized surgical technique specified in the study protocol was used with an open access technique (Hasson) below the umbilicus, followed by a standard four-port setting. Local anaesthetics were administered at all incision sites before the trocars were placed. Intra-abdominal pressure was kept at 12 mmHg or 15 mmHg in selected patients. For ultrasonic dissection, Harmonic HD1000i Shears™ (Ethicon Endosurgery [Europe] GmbH, Norderstedt, Germany) was used, set at level 3/5. The hospital’s monopolar electrocautery hook device was used for dissection, set to blend mode at 25W. The surgeon was allowed to choose the most suitable direction of dissection based on anatomical variations, the extent of inflammation and personal preference. Dissection was continued in both arms until a critical view of safety was achieved [ 24 ]. An intraoperative cholangiography was performed according to the routine in Sweden [ 25 ]. Intraoperative endoscopic removal of choledocholithiasis was recommended if common bile duct stones were encountered [ 26 ]. The cystic duct was divided with two clips on the proximal end. The division of the cystic artery was accomplished either by using clips or with the assistance of the ultrasonic device. A retrieval bag was used to extract the gallbladder.

The primary endpoint was the total complication rate, comprising all intra- and postoperatively registered complications during the first 30 postoperative days. Secondary outcomes were operating time, conversion to open surgery, length of hospital stay, readmission and use of haemostatic agents.

Randomization and blinding

After induction of anaesthesia, participants were randomly assigned to electrocautery dissection or ultrasonic dissection in a 1:1 allocation. The randomization was performed by the surgeon in a secure web-based randomization platform administered by The Information and Communication Technology Services and System Development at Umeå University, Sweden. A randomization sequence was created using a computer-generated algorithm with permuted blocks of variable sizes (4–6), stratified by centre. Until the inclusion process was finalized, the centre-specific allocation sequences were stored and accessible exclusively to the system developer. The allocation of study arms was concealed from the patient, as well as postoperative care providers and during the follow-up. No information about the allocated instrument was noted in the medical records but could be revealed for security reasons. The option of cross-over or conversion to open surgery was permitted, with documentation in the eCRF, if the surgeon deemed the allocated instrument unsafe due to inflammation or anatomical variations.

Statistical analyses

The power calculation was based on results from the phase 2b trial [ 18 ], the annual GallRiks report from 2018 [ 27 ] and clinical results from a Swedish centre specialized in ultrasonic dissection [ 28 ]. A reduction in the total complication rate from 15% with electrocautery dissection to 5% was estimated. To detect a significant difference with a power of 80% at the p < 0.05 level, 141 patients would be needed in each group. We intended to include 300 patients to accommodate dropouts and patients lost to follow-up. No interim analysis was performed as both techniques are well-established and used routinely in Sweden. Differences between the two groups were analysed using the Pearson chi-square test for categorical variables and the independent t-test or the Mann–Whitney test for continuous variables. The intention-to-treat approach was used to analyse primary and secondary outcomes. Sex and ASA grade were included as confounders in the outcome analyses to address an uneven randomization. To avoid bias from clustering of procedures performed by individual surgeons, the primary outcome was analysed using logistic generalized estimated equations (GEEs). With risk difference (RD) for treatment outcome, with 95% confidence intervals (CIs) as measures of risk. Secondary outcome analysis was performed with a similar GEE model, an independent t-test, or the Mann–Whitney test as appropriate. No data monitoring committee was involved in overseeing the data. A two-sided P -value of < 0.05 was considered significant. Statistical analysis was performed with SPSS® version 28.0 (Armonk, NY, USA, IBM Corp.).

Between September 30, 2019, and March 22, 2023, 1359 patients who met the eligibility criteria were identified at the eight participating hospitals. Because only a few surgeons at each hospital participated in the study, patients were only recruited when these surgeons were available. Two patients were excluded intraoperatively due to incomplete cholecystectomy, with one presenting extensive adhesions and one having a suspected malignancy. Of the eligible patient population, 300 were randomly assigned to treatment. In total 148 patients assigned to electrocautery dissection and 152 to ultrasonic dissection were included (Fig. 1 ). The study cohort was older with equal sex distribution, compared to the excluded cohort (Supplementary Table 1 ). The operations were performed by 25 surgeons with a median of seven procedures per surgeon (Range 1–38). Patients assigned to ultrasonic dissection were more often of male sex with a higher ASA classification (Table 1 ). Only patients with an ASA grade of ≤ 3 were included, however, two patients allocated to ultrasonic dissection were intraoperatively graded as ASA 4 by the anaesthesiologist. In addition, patients who underwent ultrasonic dissection were more often preoperatively diagnosed with moderate cholecystitis (Grade II) and were intraoperatively found to have advanced cholecystitis (Table 2 ). At inclusion, 163 (54%) patients had no history of gallstone-related symptoms, and 21 (7.0%) had a documented history of cholecystitis. The mean duration of symptoms was 3 ± 1.5 days (Table 1 ). Dissection from Calot’s triangle and upwards were most common, but the fundus-first approach was more often used with ultrasonic dissection (17.1% vs. 2.0%) (Table 2 ).

CONSORT flowchart of included patients

Primary outcome

The total complication rate was 27 (18.2%) in patients assigned to electrocautery dissection, with 2 (1.4%) suffering an intraoperative and 26 (17.1%) a postoperative complication. The corresponding data in patients assigned to ultrasonic dissection was 26 (17.1%), with 2 (1.3%) intraoperative and 25 (16.4%) postoperative complications. The adjusted total risk of complications was 18.3% (95%CI, 13.0% to 25.1%) for electrocautery and 16.7% (95%CI, 11.7% to 23.2%) for ultrasonic dissection (RD of 1.6% (95%CI, − 7.2% to 10.4%, P = 0.720). The Clavien-Dindo (CD) classification [ 29 ] was used to assign the highest score in cases of multiple postoperative complications (Table 3 ). Postoperative complications with CD > 3 were more common for electrocautery (Table 3 ). The bile duct injury in the electrocautery group can be attributed to a complicated cholangiography and a perforating catheter. The ultrasonic device was used as a complement in 13 (8.8%) patients assigned to the electrocautery dissection arm, mainly due to highly vascularized gallbladders with extensive inflammation. In the ultrasonic dissection group electrocautery was used as a supplementary measure in 14 patients (9.2%), in most cases to achieve a more precise dissection within Calot’s triangle. One patient (0.7%) underwent subtotal cholecystectomy.

Secondary outcomes

The mean operating time was 100 min (min) ± 38 for electrocautery and 99 min ± 42 for ultrasonic dissection (mean difference 1 min (95%CI − 8 min to 10 min, P = 0.816)). Four patients (2.7%) assigned to electrocautery dissection and one (0.7%) to ultrasonic dissection underwent conversion to open surgery (adjusted RD of 1.8% (95%CI − 0.8 to 4.4, P = 0.166)). The indications for conversion included advanced cholecystitis with atypical anatomy in three patients, advanced adhesions resulting from prior lower abdominal surgery in one patient and advanced cholecystitis with difficult anatomy due to obesity in one patient. The median postoperative stay was 2 days (IQR 1–2 days, range 0–23 days) for electrocautery and 1 day (IQR 1–2 days, range 0–10 days) for ultrasonic dissection ( P = 0.191). No difference was seen in readmission rates between the groups (Table 3 ). The median estimated bleeding with electrocautery dissection was 60 ml (IQR 25–100 ml), and 50 ml (IQR 20–100 ml, P = 0.312) for ultrasonic dissection. Haemostatic agents were required in 40 (27.0%) patients assigned to electrocautery and 27 (17.8%) to ultrasonic dissection (adjusted RD 10.6% (95%CI, 1.3% to 19.8%, P = 0.025)).

Other analyses

Accidental perforation of the gallbladder during dissection occurred in 77 patients (52.0%) who underwent electrocautery and in 87 patients (57.2%) who underwent ultrasonic dissection ( P = 0.364). The gallbladder was intentionally punctured by the surgeon in 93 patients (62.8%) in the electrocautery group and 98 (64.5%) in the ultrasonic dissection group with gallbladder distention and difficulty in grasping listed as the most common causes. The cystic artery was ligated with clips in 115 patients (77.7%) who underwent electrocautery and 84 patients (54.9%) who underwent ultrasonic dissection. The ultrasonic dissector was used to ligate the artery in 54 patients (35.5%) in the latter group. No significant difference in the use of thrombosis prophylaxis was demonstrated (Table 2 ). A successful cholangiography was performed in 145 patients (98.0%) assigned to electrocautery and 141 (92.8%) allocated to ultrasonic dissection, with detection of common bile duct stones in 14 patients (9.5%) who underwent electrocautery dissection and 21 (13.8%) operated with ultrasonic dissection. Intraoperative ERCP was the most frequent method for stone removal, used in 9 patients (64.3%) allocated to electrocautery and 16 (76.2%) allocated to ultrasonic dissection. There was no discernible connection between the fundus-first approach and the increased rate of CBDS during ultrasonic dissection.

This multicentre RCT shows that ultrasonic dissection is a safe alternative to electrocautery dissection in laparoscopic cholecystectomies for emergency surgery patients with acute cholecystitis. The intra- and postoperative complication rates were comparable in both groups, suggesting that the techniques are safe for patients with mild-to-moderate acute cholecystitis. Patients randomized to ultrasonic dissection were predominantly male sex with higher ASA classification and exhibited a more advanced stage of inflammation. The presence of male sex and the extent of inflammation are known risk factors for complex procedures and the need for conversion to open surgery [ 30 , 31 ]. Despite this, ultrasonic dissection reduced the use of additional haemostatic agents, although no significant difference in estimated blood loss was observed. Furthermore, a trend was noted among surgeons to prefer ultrasonic dissection over electrocautery in patients with extensive inflammation. This suggests that ultrasonic dissection may serve as a complement to electrocautery in cases of advanced inflammation prior to conversion to open surgery, or as a first-line approach in patients with complicated acute cholecystitis.

No significant reduction in operating time, hospital stays or gallbladder perforations was seen, which has been found for ultrasonic dissection in elective surgery [ 1 , 2 , 3 , 4 , 5 , 6 , 7 , 8 , 9 , 10 , 11 ]. The gallbladder perforation rates were high and slightly exceeded those reported in a Swedish observational study, which demonstrated a perforation rate of 48% in acute cholecystitis [ 32 ]. However, the higher rates align with expectations for a randomized controlled trial focusing on adverse outcomes. The reduced need for haemostatic agents supports previous studies on acute cholecystitis, indicating less bleeding with ultrasonic dissection [ 15 , 33 ]. However, in contrast to these studies, our findings did not indicate a significant reduction in estimated blood loss or conversions to open surgery, and the conversion rate was low overall. Intraoperative blood loss is challenging to measure accurately in laparoscopic surgery, and the amount of bleeding during acute cholecystectomies can vary significantly. Therefore, the use of haemostatic agents may serve as a reliable indicator of intraoperative bleeding in this context. The decreased need for haemostatic agents strengthens previous studies demonstrating reduced indirect and direct costs with ultrasonic dissection in elective surgery [ 34 , 35 , 36 ]. The challenges associated with instrument handling during the learning curve are often cited as another drawback of ultrasonic dissection. In the pilot study, we showed that the fundus first technique with ultrasonic dissection has a low complication rate for residents and specialists in the first 15 operations [ 18 ]. The fundus-first approach was used in the pilot study because it is the preferred method at Sweden´s leading center for ultrasonic dissection in gallbladder surgery [ 1 , 2 ]. This technique has been linked to low complication rates, including a minimal incidence of bile duct injuries (0.07%) [ 28 ]. Consequently, the ultrasonic instrument and the fundus-first technique were closely associated during the initial study. However, surgeons in the pilot study still often preferred to start the dissection from the triangle of Calot to identify crucial structures [ 18 ]. Given the complex anatomy and advanced inflammation in acute cholecystitis, surgeons in this study were allowed to choose the direction of the dissection based on their intraoperative assessment. Crossover occurred in less than one-tenth of patients in each arm. For ultrasonic dissection, electrocautery was used when dissecting the triangle of Calot, where the ultrasonic instrument may be considered blunt. Conversely, in the electrocautery group, the ultrasonic dissector was used more extensively to separate the gallbladder from the liver in cases of advanced inflammation. Given that an intention-to-treat analysis was employed, the potential for underestimating the results cannot be ruled out. In the pilot study the older version of the instrument was used (Harmonic ACE + (Ethicon Endosurgery [Europe] GmbH, Norderstedt, Germany), which many surgeons considered too blunt when dissecting the structures within the Calot’s triangle. We used the slimmer and slightly curved instrument in this study (Harmonic HD1000i Shears™ (Ethicon Endosurgery [Europe] GmbH, Norderstedt, Germany).

The study’s strength lies in its design as a randomized, double-blinded, parallel-group controlled trial conducted at eight hospitals in Sweden, involving 25 surgeons from university clinics, regional hospitals, and county hospitals. The study was preceded by a phase 2b pilot study on 240 elective cholecystectomies to evaluate the technique and safety of the procedure [ 18 ]. Intraoperative randomization, concealment of the allocated treatment, blinding of patients, postoperative caregivers and follow-up personnel and intention-to-treat analysis mitigate the risk of systematic errors. The study is, however, not without limitations. Because only surgeons with previous experience in both techniques could operate, 1059 eligible patients were not included in the study. The power calculation was based on a hypothetical significant reduction in complication rates based on best available data at the time [ 27 , 28 ]. Concerning the results of this study, the potential safety effects of the intervention are likely smaller, suggesting that the study may have been underpowered to detect differences. Still, the present study shows comparable safety outcomes between ultrasonic dissection and standard treatment with electrocautery dissection. Despite randomization, the ultrasonic group included a higher proportion of male patients with higher ASA classification and patients with more advanced cholecystitis. Most participating surgeons had more experience in electrocautery dissection. We cannot rule out the possibility that ultrasonic dissection when performed by highly skilled surgeons who have surpassed the initial learning phase, could have resulted in varying rates of complications. All registered complications were included in the outcome analysis, but it is unlikely that all complications can be attributed to the allocated instrument. The intraoperative findings were based on subjective observation and no objective measure of difficulty, such as the Parkland grading system, was employed [ 37 ].

Despite evidence supporting the superiority of ultrasonic dissection over electrocautery in elective cholecystectomies [ 1 , 2 , 3 , 4 , 5 , 6 , 7 , 8 , 9 , 10 , 11 , 15 , 33 ], the technique is still not implemented in general practice. The reluctance to apply the technique may stem from its association with the fundus-first approach and a potentially increased rate of severe vascular and bile duct injuries [ 38 ]. In addition, the unfavourable reputation could be attributed to a notable rise in bile duct injuries following the implementation of the laparoscopic technique, particularly when used as a second-line approach in complicated cases [ 39 ]. Ultrasonic dissection is technically somewhat different from electrocautery dissection, necessitating training to achieve mastery of the technique. Based on our experience from the pilot work and the current study, we recommend that the technique is practiced in elective and less complicated cholecystectomies before it is used in complicated cases. We deem it wise to uphold a critical view of safety, regardless of the direction of the dissection [ 24 , 40 ]. Another concern with ultrasonic devices relates to increased instrumental costs. To fully evaluate the benefits of ultrasonic dissection in acute cholecystectomies, further studies should include cost analyses and patient-reported outcomes. The results highlight the challenges of addressing differences in adverse events within a randomised controlled trial in emergency surgery, particularly when involving a reasonable number of patients. Based on our findings, both instruments can be considered safe for use in patients with acute cholecystitis. However, whether ultrasonic dissection should become the standard approach, or remain an alternative is a question for future studies. Future research should aim to assess the long-term outcomes and cost-effectiveness of ultrasonic dissection compared to traditional techniques, which will aid in guiding clinical decision-making in the management of acute cholecystitis.

This randomized controlled trial demonstrates that ultrasonic dissection and electrocautery dissection have comparable complication risks in emergency surgery patients with mild-to-moderate acute cholecystitis. Ultrasonic dissection can serve as an alternative to, or adjunct with, electrocautery dissection in laparoscopic cholecystectomy for acute cholecystitis.

Availability of data and materials

The datasets used and analysed during the current study are available from the corresponding author on reasonable request.

Abbreviations

Swedish Registry of Gallstone Surgery and Endoscopic Retrograde Cholangiopancreatography

American Society of Anaesthesiologists physical status classification score

Electronic case report form

Endoscopic retrograde cholangiopancreatography

Generalized estimated equations

Risk difference

Confidence interval

Interquartile range

Clavien–Dindo classification

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Acknowledgements

The authors thank Anna Nordin and Michaela Breistrand, research nurses at Mora Hospital, for their assistance with 30-day follow-up and document management; Riccardo Lo Martire, Statistician, for statistical advice; and Dr Leslie Shaps, independent consultant, for proofreading the manuscript. We also thank all participating surgeons.

Open access funding provided by Karolinska Institute. This study has been financed by a grant from the Regional Research Council Mid Sweden (RFR-980175), Centre for Clinical Research, Falun, Sweden (CKFUU-96329, CKFUU-9692) and research funding according to the Swedish ALF agreement (Stockholm County, 20190336).

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Contributions

MB, GS, LE, YC, JH and JÖ conceptualized and designed the study. MB administered the study and oversaw data collection. Data acquisition was performed by MB, YC, HB, JH, ADP, KB and JÖ. MB and GS performed the data analysis. MB, GS, LE, YC, HB, JH, ADP, ES, KB and JÖ interpreted the data. Funding was acquired by MB, GS, ES and JÖ. MB wrote the main manuscript text and prepared all tables and figures. All authors contributed to the editing and review of the manuscript. All authors have read and approved the final manuscript.

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Correspondence to My Blohm .

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The study was approved by the Regional Research Ethics Committee in Stockholm, Sweden (2016/1434–31/4, 2018/2587–32). Oral and written informed consent was retrieved from all participants.

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Competing interests

Drs. Blohm, Österberg and Sandblom are present board members for the Swedish Registry of Gallstone Surgery and Endocopic Retrograde Cholangiopancreatography. Dr Blohm is a board member of the Swedish Society of Emergency Surgery and Traumatology. Dr Johanna Österberg is a board member of the Swedish Register of Hernia Surgery. Dr Stenberg have received consultant fees from Johnson & Johnson Medical paid to the institution for work unrelated to the present manuscript. For the remaining authors none were declared.

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Blohm, M., Sandblom, G., Enochsson, L. et al. Ultrasonic dissection versus electrocautery dissection in laparoscopic cholecystectomy for acute cholecystitis: a randomized controlled trial (SONOCHOL-trial). World J Emerg Surg 19 , 34 (2024). https://doi.org/10.1186/s13017-024-00565-4

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General surgery
Acute care surgery
Acute cholecystitis
Minimally invasive surgical procedures
Laparoscopic cholecystectomy
Electrosurgery
Ultrasonic surgical procedures
Electrocoagulation

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Random assignment is essential because it increases the likelihood that the groups are the same at the outset. With all characteristics being equal between groups, other than the application of the independent variable, any differences found between group outcomes can be more confidently attributed to the effect of the intervention.
Random assignment
Random assignment is a technique used in experiments to ensure that participants are placed into different groups in a way that is entirely based on chance. This method helps eliminate bias and ensures that each group is similar at the start of the experiment, allowing for a more valid comparison of outcomes between groups. It is a critical feature in the design of experiments, as it helps to ...
Random Assignment
Random assignment helps eliminate selection bias, ensuring that differences between groups are due to the experimental treatment rather than other variables. This technique is crucial for internal validity, as it strengthens causal inferences by demonstrating that changes in outcomes can be attributed to the manipulated variables.
Random Assignment
Random assignment, therefore, also provides a "safeguard" for the researcher, protecting him from letting his wishes or opinions (unconsciously) influence the outcome of a study by systematically assigning different types of participants to particular groups (Gigerenzer et al. 1989).
PDF Random Assignment
Outline 1. Random Assignment Û Deﬁnition Û Identiﬁcation of Common Causal Parameters 2. Case Study: Gneezy et al. (2019) Û Deﬁnition of the ATE Û ATE Identiﬁcation under Random Assignment Û Construction and Analysis of ATE‰ Û Hypothesis Testing 3. Evaluating Random Assignment 4. Binning Estimators These notes beneﬁt greatly from the lecture notes of Prof. Alex Torgovitsky.
Random Assignment in Psychology (Definition + 40 Examples)
A hidden hero in this adventure of discovery is a method called random assignment, a cornerstone in psychological research that helps scientists uncover the truths about the human mind and behavior. ... Researchers were keen to understand the impact of different teaching methods on student outcomes. By randomly assigning students to various ...
4.23 Independence assumption & random assignment
Independence assumption & random assignment. Random assignment. = a statistical solution (Holland 1986, 948f) Units randomly assigned to treatment/control have identical distributions of covariates/potential outcomes in both groups ((infinite) long run!) 25. Random assignment induces independence between treatment status and potential outcomes.
Elements of Research : Random Assignment
Research staff must follow random assignment protocol, if that is part of the study design, to maintain the integrity of the research. Failure to follow procedures used for random assignment prevents the study outcomes from being meaningful and applicable to the groups represented. Case example of random assignment
15 Random Assignment Examples
Random Assignment Examples. 1. Pharmaceutical Efficacy Study. In this type of research, consider a scenario where a pharmaceutical company wishes to test the potency of two different versions of a medication, Medication A and Medication B. The researcher recruits a group of volunteers and randomly assigns them to receive either Medication A or ...
Random Assignment in Psychology (Intro for Students)
Random assignment ensures that these individual differences are spread out equally among the experimental groups, making it less likely that they will unduly influence the outcome. Temporal or Time-Related Confounds: Events or situations that occur at a particular time can influence the outcome of an experiment.
Random Assignment
Random Assignment - In a Nutshell. Random assignment is where you randomly place research participants into specific groups. This method eliminates bias in the results by ensuring that all participants have an equal chance of getting into either group. Random assignment is usually used in independent measures or between-group experiment designs.
Random Assignment in Experiments
Random sampling (also called probability sampling or random selection) is a way of selecting members of a population to be included in your study. In contrast, random assignment is a way of sorting the sample participants into control and experimental groups. While random sampling is used in many types of studies, random assignment is only used ...
econometrics
11. Random assignment is valuable because it ensures independence of treatment from potential outcomes. That is how it leads to unbiased estimates of the average treatment effect. But other assignment schemes can also systematically ensure independence of treatment from potential outcomes.
Random Assignment
Random Assignment: Implementation in Complex Field Settings. R.G. St. Pierre, in International Encyclopedia of the Social & Behavioral Sciences, 2001 Random assignment of units to treatment/control groups allows researchers to make the strongest possible causal connection between the treatment and observed outcomes. This article considers the way in which random assignment is implemented in ...
Ultrasonic dissection versus electrocautery dissection in laparoscopic
The primary outcome was analysed using logistic generalized estimated equations. Patients, postoperative caregivers, and follow-up personnel were blinded to group assignment. From September 2019 to March 2023, 300 patients were enrolled and randomly assigned to electrocautery dissection (n = 148) and ultrasonic dissection (n = 152).

Random Assignment in Psychology: Definition & Examples

Importance

Random Selection vs. Random Assignment

Random Assignment vs Random Sampling

When to Use Random Assignment

How to Use Random Assignment

When is Random Assignment not used?

Drawbacks of Random Assignment

What is the difference between random sampling and random assignment?

Does random assignment increase internal validity?

Does random assignment reduce sampling error?

When is random assignment not possible?

Does random assignment eliminate confounding variables?

Why is random assignment of participants to treatment conditions in an experiment used?

Further Reading

Purpose and Limitations of Random Assignment

How does random assignment produce comparable groups?

2. Random assignment prevents confounding

3. Random assignment also eliminates other threats to internal validity

What if random assignment produced unequal groups?

Limitations of random assignment

1. Ethical issues:

2. Low external validity:

3. Higher cost of implementation:

4. Impracticality when answering non-causal questions:

5. Impracticality when studying the effect of variables that cannot be manipulated:

6. Difficulty to control participants:

Further reading

The Definition of Random Assignment According to Psychology

Random Assignment In Research

Random Selection

Example of Random Assignment

A Word From Verywell

Experimental Design

5 Must Know Facts For Your Next Test

Review Questions

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Random Assignment

Introduction

Why Is Random Assignment Crucial for Statistical Inference?

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Applied Causal Analysis (with R)

Random Assignment in Psychology (Intro for Students)

Why Researchers Use Random Assignment

Fact File: Experiments 101

Methods of Random Assignment

1. Random number generator

2. Flipping a coin

3. Rolling a die

4. Condition names in a hat

Potential Confounding Effects

Limitations of the Random Assignment Procedure

Applications of Random Assignment

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Random Assignment – A Simple Introduction with Examples

Random Assignment – In a Nutshell

Definition: Random assignment

Importance of random assignment

Random assignment vs. random sampling

How to use random assignment

Random assignment in block experimental designs

When random assignment is not used

Comparing different groups

No ethical justifiability

What is the definition of random assignment?

When is random assignment applicable?

What is the importance of random assignment?

When should you NOT use random assignment