Compensatory Approach to Selection Decisions & Multiple Linear Regression

In this video, I explain how regression coefficient estimates from a multiple linear regression model can be used to predict criterion scores. This video is meant to provide a foundation for understanding how, in an employee selection context, organizations can (a) estimate a multiple linear regression model based on data from a validation study sample for 2+selection tools (e.g., personality test, structured interview) and a criterion (e.g., job performance), (b) construct an equation to based on the model coefficient estimates based on that validation sample data, and (c) apply the equation to future applicant scores on the selection tools in order to predict their criterion scores. This approach is referred to as a compensatory approach to making employee selection decisions.
For a conceptual overview of multiple linear regression, check out: • Multiple Linear Regres...
For an introduction to employee selection, check out: • Applying a Compensator...
For an overview of how we can evaluate employee selection tools, check out: • Evaluating Selection T...
To learn how to use R to a estimate a multiple linear regression, including evaluating whether statistical assumptions have been met, check out: • Multiple Linear Regres...
To learn how to use R to a estimate a multiple linear regression, with an emphasis on interpreting incremental validity, check out: • Evaluating Incremental...
To learn how to use R to estimate a multiple linear regression model in order to predict criterion scores, which is part of applying a compensatory approach to making selection decisions, check out: • Applying a Compensator...