What does it mean when participants are randomly selected?

The word “random” has a precise meaning in statistics. Random selection doesn’t just mean you can just randomly pick a few items to make up a sample. That method is actually something called haphazard sampling, where you try to create a random sample by haphazardly choosing items in order to try and recreate true randomness. That doesn’t usually work (because of something called selection bias). In order to create a true random selection, you need to use one of the tried and testing random selection methods, like simple random sampling.

Example of random selection: You are studying test taking behaviors at a college of 5,000 students. You choose every 50th student from a list (a random selection method called systematic sampling) to create a sample of 50 students to study.

Example of non random selection:
From the same list of 5,000 students, you randomly circle 50 names. This isn’t truly random as your biases (known or unknown) could affect who you circle. For example, you might unknowingly circle boys names over girls, or American-sounding names over foreign-sounding names.

What is Random Assignment?

Random assignment is where study participants are randomly assigned to a study group (i.e. an experimental group or a control group). In a single blind study, the participant does not know whether they are in the experimental group or the control group. In a double blind study, neither the participant nor the researcher knows.

Example of random assignment: you have a study group of 50 people and you write their names on equal size balls. You then place the balls into an urn and mix them well (this is a classic ball and urn experiment). The first 25 balls you draw go into the experimental group. The rest go into the control group.

Example of non-random assignment: you have a list of 50 people to assign to control groups and experimental groups. You use your knowledge and experience to choose 25 people who you think would be better suited to the experimental group (a method called purposive sampling).

Random selection refers to a process that researchers use to pick participants for a study. When using this method, every single member of a population has an equal chance of being chosen as a subject. This process is an important research tool used in psychology research, allowing scientists to create representative samples from which conclusions can be drawn and applied to the larger population.

Random Selection vs. Random Assignment: What’s the Difference?

One thing that is important to note is that random selection is not the same thing as random assignment. While random selection involves how participants are chosen for a study, random assignment involves how those chosen are then assigned to different groups in the experiment. Many studies and experiments actually use both of these techniques.

For example, random selection might be used to draw 100 students to participate in a study. Each of these 100 participants would then be randomly assigned to either the control group or the experimental group.

Face validity and content validity are similar in that they both evaluate how suitable the content of a test is. The difference is that face validity is subjective, and assesses content at surface level.

When a test has strong face validity, anyone would agree that the test’s questions appear to measure what they are intended to measure.

For example, looking at a 4th grade math test consisting of problems in which students have to add and multiply, most people would agree that it has strong face validity (i.e., it looks like a math test).

On the other hand, content validity evaluates how well a test represents all the aspects of a topic. Assessing content validity is more systematic and relies on expert evaluation. of each question, analyzing whether each one covers the aspects that the test was designed to cover.

A 4th grade math test would have high content validity if it covered all the skills taught in that grade. Experts(in this case, math teachers), would have to evaluate the content validity by comparing the test to the learning objectives.

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.

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Why does random assignment matter?

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.

Example: Different levels of an independent variableIn a clinical trial, you investigate the effect of iron supplements (your independent variable) on energy levels (your dependent variable).

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.

Example: Non-random assignmentIn your clinical study, you recruit participants using flyers at gyms, cafes, and local community centers. You use a haphazard method to assign participants to groups based on the recruitment location:

• 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.

If your study outcomes show more energy in the high dosage group, you might not be able to attribute this result solely to your independent variable manipulation (the iron supplement). Instead, this result may come from the interaction between the participants’ characteristics and the independent variable.

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 vs random assignment

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.

Example: Random samplingYou’re studying new interventions for boosting employee engagement in a large company.

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.

By using a random sample, you can be reasonably confident that your results are applicable across the whole company.

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.

Example: Random assignmentIn your study, you have two groups:

• 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.

By using random assignment, you can be reasonably confident that any differences in employee engagement outcomes are an effect of the team-building intervention (and not caused by other differences between the groups).

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How do you use random assignment?

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.

When is random assignment not used?

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.

Frequently asked questions about random assignment

What is random assignment?

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.

What’s the difference between random assignment and random selection?

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.

When do you use random assignment?

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.

How do you randomly assign participants to groups?

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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Bhandari, P. (2022, December 05). Random Assignment in Experiments | Introduction & Examples. Scribbr. Retrieved January 2, 2023, from https://www.scribbr.com/methodology/random-assignment/

What does randomly selected mean?

A sample selected from a finite population is said to be random if every possible sample has equal probability of selection.

What is random selection of participants?

Definition: Random selection is the process of selecting a smaller group of individuals from a larger group to be participants in a study. Every person has an equal chance of being selected, which allows each of the individuals in the group the same chance of participating.

Why randomly select participants?

Why do researchers utilize random selection? The purpose is to increase the generalizability of the results. By drawing a random sample from a larger population, the goal is that the sample will be representative of the larger group and less likely to be subject to bias.

What does it mean to randomize participants to groups?

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.