Random Assignment of Participants

Bias is an inherent part of the research process, and scholars must proactively address sources of bias to ensure validity. While bias has the potential to impact each stage of the research process, how participants are assigned to experimental groups is an important part of research design, as selection bias may be introduced. With selection bias, certain members of a sample population are intentionally omitted or targeted based on a specific trait(s). To reduce selection bias, random assignment of participants is used.

With random assignment, participants have an equal chance of being assigned to an experimental or control group, resulting in a sample that is, in theory, representative of the population. Random assignment helps ensure comparable groups, minimizing the influence of individual characteristics, such as age, race, gender identification, and countless other variations in the population. Moreover, noted differences between groups are most likely due to chance and not the result of an unmeasured or unknown variable or sampling error. Researcher bias is significantly reduced because the researcher does not control group assignment. In addition, many of the most common statistical tests assume random sampling. Last, random assignment protects internal validity. Internal validity is critical when establishing cause-effect relationships (i.e., variable A caused the change in variable B). This entry introduces different random sampling techniques, including simple random sampling, stratified, cluster, systematic, and multistage. In addition, the lack of random sampling in qualitative research is discussed.