Random Assignment

Random assignment is a technique for assigning participants to experimental conditions and a prerequisite of true experimental designs. It requires the use of randomization methods to place participants of a particular study into experimental conditions (e.g., treatment vs. control). It ensures that each participant has an equal chance of being placed into either of the experimental groups.

Systemic differences at the outset of an experiment can hurt internal validity—the degree to which effects of the experiment can be attributed solely to the experimental treatment. The random assignment of study members into groups is a requirement for alleviating any initial systemic differences between experimental groups. However, random assignment alone is not a guarantee that there won’t be any initial differences between groups, but rather that any initial differences won’t be systemic.

Random assignment is commonly confused and used interchangeably with random selection. However, the terms denote different foci. Random assignment refers to the method by which study participants are randomly assigned to experimental conditions. By comparison, random selection refers to the method by which the sample is selected from the population for inclusion in a particular study.

[Page 1366]Although random assignment is a necessary component of an experimental design, random selection can be used with any research design. However, for an experiment, random assignment would typically follow after random selection has occurred.

There are two distinct forms of random assignment: simple and matched. Simple random assignment ensures that the participants are independently assigned to an experimental condition. Although simple random assignment improves internal validity, the experiment may be vulnerable to extraneous variables (i.e., individual differences). Matched random assignment controls for individual differences by pairing participants in “sets” based on a shared characteristic and subsequently assigning them to different experimental conditions. If an experiment has multiple conditions or the sample size is relatively small, participants can be allocated in “blocks” to ensure equal sample size distribution (block randomization).

Simple random assignment could be achieved using a computerized randomizer or manual technique (e.g., flipping a coin). However, in the cases of small samples or possible confounding variables, a researcher would use the block or matched random assignment. For example, if a researcher wanted to examine the effect of a new curriculum on academic performance, participants could be paired into sets based on GPA and then randomly assigned to the experimental conditions. By pairing the sets based on GPA, the researchers can avoid an unequal distribution of skill in either condition.

See also Experimental Designs; Generalizability; Random Selection; Threats to Research Validity; Validity; Validity Generalization