A common research problem in validation studies is the estimation of the population correlation between predictor X and performance Y from a non-randomly selected sample. Procedures for getting unbiased estimates of population correlations in a limited set of conditions in which no rejection of job offers is assumed have been developed. However, in applied selection settings, it is very likely that some of the candidates who have received job offers reject them through a self-selection process. If an estimation model based on the assumption that there is no rejection of job offers via self-selection is used, estimates of population parameters may be biased due to model misspecification. In the current study, a procedure is developed that is applicable to a variety of realistic validation settings, including a setting in which both institutional selection and applicant's rejection of job offers are involved. Data requirements of the procedure are also discussed.
- Non-ignorable selection process
- Population correlation
- Range restriction
- Validation study