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- Random Assignment in Experiments | Introduction & Examples
Random Assignment in Experiments | Introduction & Examples
Published on March 8, 2021 by Pritha Bhandari . Revised on February 13, 2023.
In experimental research, random assignment is a way of placing participants from your sample into different treatment groups using randomization.
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 randomized 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, not research biases like sampling bias or selection bias .
Table of contents
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 and avoid biases.
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, to control for a placebo effect ),
- 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 ways at the start of the experiment, as this can seriously affect (and even invalidate) your work.
If you don’t use random assignment, you may not be able to rule out alternative explanations for your results.
- participants recruited from cafes are placed in the control group ,
- participants recruited from local community centers 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 behaviors than people who frequent cafes or community centers, 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.
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 generalizability of your results, because it helps 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 8000 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.
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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 in 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 dice 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 randomized block design involves placing participants into blocks based on a shared characteristic (e.g., college students versus 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 men and women 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, etc.). 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 behaviors, 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 randomization. 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 generalizability 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 dice to randomly assign participants to groups.
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The Definition of Random Assignment According to Psychology
Kendra Cherry, MS, is an author and educational consultant focused on helping students learn about psychology.
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.
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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. Study participants are randomly assigned to different groups, such as the experimental group or treatment group.
Random assignment might involve tactics such as flipping a coin, drawing names out of a hat, rolling dice, or assigning random numbers to participants.
It is important to note that random assignment differs from random selection . While random selection refers to how participants are randomly chosen to represent the larger 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 lead to changes in another variable, psychologists must perform an experiment. Researchers often begin by forming a testable hypothesis predicting that one variable of interest will have some 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 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.
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 51% female and 49% 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. Once a pool of participants has been selected, it is time to assign them into groups.
By randomly assigning the participants into groups, the experimenters can be fairly sure that each group will be the same before the independent variable is applied.
Participants might be randomly assigned to the control group , which does not receive the treatment in question. Or they might be randomly assigned to the experimental group , which does receive the treatment.
Random assignment increases the likelihood that the two groups are the same at the outset. That way any changes that result from the application of the independent variable can be assumed to be the result of the treatment of interest.
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 population 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. 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.
Sullivan L. Random assignment versus random selection . In: The SAGE Glossary of the Social and Behavioral Sciences. Thousand Oaks: SAGE Publications, Inc.; 2009. doi:10.4135/9781412972024.n2108
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
Alferes VR. Methods of Randomization in Experimental Design. Los Angeles: SAGE; 2012.
Nestor PG, Schutt RK. Research Methods in Psychology: Investigating Human Behavior. Los Angeles: SAGE; 2015.
By Kendra Cherry Kendra Cherry, MS, is an author and educational consultant focused on helping students learn about psychology.
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Introduction to Random Assignment
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What is Random Assignment?
The sample groups used in experimental research are often divided into two groups, the control group and the treatment group. Both these groups are identical in all ways, the only difference being that the treatment group receives the treatment being tested while the control group receives a placebo or nothing at all.
Random assignment is used in experimental research to assign participants to either group using randomization. Therefore, it involves dividing the sample group into the treatment group and the control group using a completely random process. Random assignment is integral to experimental design as it helps construct groups that are comparable.
The Significance of Random Assignment in Experimental Research
Random assignment helps build the internal validity of your study as it plays an integral role in controlling different variables, even those that are extraneous.
It helps eliminate any potential sources of bias within the study, and also makes it easier to generalize the results of a study to the larger population. It does so by ensuring members of each group are the same, making them more representative of the larger population, enhancing the external validity of the study in the process.
The Difference between Random Assignment and Random Sampling
Random sampling, also known as probability sampling, refers to a broad category of sampling techniques that all involve selecting participants for the sample group using random selection processes.
The concepts of random selection and random assignment are often confused and it is important to understand the difference between the two. Random sampling is used to select participants from your target population to be included in the sample group of your study. Random assignment, on the other hand, involves dividing this sample group into two; the treatment/experimental group and the control group.
Random sampling is often used in many different types of studies, while random assignment is specifically used in between-subjects experimental designs.
There are studies that employ the use of both, some that employ the use of only one, and some that employ the use of neither (cases where non-probability sampling techniques are used in studies that don’t require random assignment).
Random sampling increases the external validity of your research while random assignment increases the internal validity of your study. This is because:
- Random sampling allows you to select an unbiased sample that is representative of the larger population and is, therefore, more generalizable, enhancing the external validity of your research.
- Random assignment helps ensure that the systematic differences between both groups are minimized or eliminated, allowing you to attribute any differences between the groups to the independent variable itself (the treatment). This increases the internal validity of the research.
Simple Ways to use Random Assignment
Random assignment can be conducted using very simple techniques. You can start off by assigning a unique number to each member of the sample group. Then, you can use a manual method or an automated method to randomly assign participants to either group. Let’s take a look at some of the different methods used to do so:
This involves placing every number token in a container and then drawing out numbers at random to be assigned to each group.
Random Number Generator:
There are certain computer programs that allow you to generate random numbers. You input all the unique numbers used to label participants, and the program will generate random numbers for you to assign to either group.
If you need to divide your sample into just two groups, you can flip a coin for each number to assign participants into either group.
When is Random Assignment Inappropriate ?
There are certain cases where random assignment is not applicable or not ethical to employ.
In cases where researchers are studying unhealthy or dangerous behaviours, it is unethical to employ the use of random assignment as it would need to involve the manipulation of unhealthy habits within participants, deteriorating their health in the process. In such cases, quasi-experimental studies can be used. These are studies that do not rely on random assignment, and instead, group participants based on whether they are receiving the treatment or not (without your intervention).
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Some studies aim to find differences between participants with certain characteristics. For instance, gender. In such cases, random assignment cannot be used to divide the sample group as participants need to be assigned to groups based on specific characteristics. While studying the difference between men and women, the groups will have to be categorized based on gender.
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Difference between Random Selection and Random Assignment
Random selection and random assignment are commonly confused or used interchangeably, though the terms refer to entirely different processes. Random selection refers to how sample members (study participants) are selected from the population for inclusion in the study. Random assignment is an aspect of experimental design in which study participants are assigned to the treatment or control group using a random procedure.
Random selection requires the use of some form of random sampling (such as stratified random sampling , in which the population is sorted into groups from which sample members are chosen randomly). Random sampling is a probability sampling method, meaning that it relies on the laws of probability to select a sample that can be used to make inference to the population; this is the basis of statistical tests of significance .
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Random assignment takes place following the selection of participants for the study. In a true experiment, all study participants are randomly assigned either to receive the treatment (also known as the stimulus or intervention) or to act as a control in the study (meaning they do not receive the treatment). Although random assignment is a simple procedure (it can be accomplished by the flip of a coin), it can be challenging to implement outside of controlled laboratory conditions.
A study can use both, only one, or neither. Here are some examples to illustrate each situation:
A researcher gets a list of all students enrolled at a particular school (the population). Using a random number generator, the researcher selects 100 students from the school to participate in the study (the random sample). All students’ names are placed in a hat and 50 are chosen to receive the intervention (the treatment group), while the remaining 50 students serve as the control group. This design uses both random selection and random assignment.
A study using only random assignment could ask the principle of the school to select the students she believes are most likely to enjoy participating in the study, and the researcher could then randomly assign this sample of students to the treatment and control groups. In such a design the researcher could draw conclusions about the effect of the intervention but couldn’t make any inference about whether the effect would likely to be found in the population.
A study using only random selection could randomly select students from the overall population of the school, but then assign students in one grade to the intervention and students in another grade to the control group. While any data collected from this sample could be used to make inference to the population of the school, the lack of random assignment to be in the treatment or control group would make it impossible to conclude whether the intervention had any effect.
Random selection is thus essential to external validity, or the extent to which the researcher can use the results of the study to generalize to the larger population. Random assignment is central to internal validity, which allows the researcher to make causal claims about the effect of the treatment. Nonrandom assignment often leads to non-equivalent groups, meaning that any effect of the treatment might be a result of the groups being different at the outset rather than different at the end as a result of the treatment. The consequences of random selection and random assignment are clearly very different, and a strong research design will employ both whenever possible to ensure both internal and external validity .
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Random Assignment – A Simple Introduction with Examples
How do you like this article.
Completing a research or thesis paper is more work than most students imagine. For instance, you must conduct experiments before coming up with conclusions. In experimental studies, the random assignment of participants is a vital element, which this article will discuss.
- 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. 1 2
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: 3
- 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 1
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. 4
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. 5
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. 1
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. 3
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.
1 Smith, Thomas. “Random Assignment in Experiments.” AssignmentHelp. September 16, 2021. https://www.totalassignmenthelp.com/blog/random-assignment/ .
2 ScienceDirect. “Pearson Correlation.” Accessed October 20, 2022, https://www.sciencedirect.com/topics/computer-science/pearson-correlation .
3 Frost, Jim. “Random Assignment in Experiments.” Statistics By Jim. Accessed October 20, 2022. https://statisticsbyjim.com/basics/random-assignment-experiments/ .
4 David. “Random Sampling vs. Random Assignment.” Statistics Solutions. Accessed October 20, 2022. https://www.statisticssolutions.com/random-sampling-vs-random-assignment/ .
5 Cherry, Kendra. “The Definition of Random Assignment According to Psychology.” April 21, 2020. https://www.verywellmind.com/what-is-random-assignment-2795800 .
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In an experiment, random assignment means placing your participants into control and experimental groups at random.
Random assignment is a procedure used in experiments to create multiple study groups that include participants with similar characteristics so that the groups
Random assignment refers to the use of chance procedures in psychology experiments to ensure that each participant has the same opportunity
Random assignment or random placement is an experimental technique for assigning human participants or animal subjects to different groups in an experiment
Random assignment is used in experimental research to assign participants to either group using randomization. Therefore, it involves dividing the sample
Random assignment refers to the method you use to place participants into groups in an experimental study. For example, say you are conducting a study comparing
Random selection refers to how sample members (study participants) are selected from the population for inclusion in the study. Random assignment is an
What is the definition of random assignment? ... It is an experimental research technique that involves randomly placing participants from your
Random assignment uses a chance process to assign subjects to experimental groups. Using random assignment requires that the experimenters can control the group
in experimental design, the assignment of participants or units to the different conditions of an experiment entirely at random, so that each unit or