Explanation[edit]

Self-selection makes determination of causation more difficult. For example, when attempting to assess the effect of a test preparation course in increasing participant's test scores, significantly higher test scores might be observed among students who choose to participate in the preparation course itself. Due to self-selection, there may be a number of differences between the people who choose to take the course and those who choose not to, such as motivation, socioeconomic status, or prior test-taking experience. Due to self-selection according to such factors, a significant difference in mean test scores could be observed between the two populations independent of any ability of the course to affect test scores. An outcome might be that those who elect to do the preparation course would have achieved higher scores in the actual test anyway. If the study measures an improvement in absolute test scores due to participation in the preparation course, they may be skewed to show a higher effect. A relative measure of 'improvement' might improve the reliability of the study somewhat, but only partially.


Self-selection bias causes problems for research about programs or products. In particular, self-selection affects evaluation of whether or not a given program has some effect, and complicates interpretation of market research.


The Roy model provides one of the earliest academic illustrations of the self-selection problem.