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.
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:
Reds = 12
Reds = 5
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:
Reds = 4
Reds = 5
To achieve better balance in our two conditions, we use randomized sampling.
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.
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.
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