Using the Errors-in-Variables Method in Two-Group Pretest-Posttest Designs

Abstract

Culpepper and Aguinis (2011) highlighted the benefit of using the errors-in-variables (EIV) method to control for measurement error and obtain unbiased regression estimates. The current study investigated the EIV method and compared it to change scores and analysis of covariance (ANCOVA) in a two-group pretest-posttest design. Results indicated that the EIV method’s estimates were unbiased under many conditions, but the EIV method consistently demonstrated lower power than the change score method. An additional risk with using the EIV method is that one must enter the covariate reliability into the EIV model, and results highlighted that estimates are biased if a researcher chooses a value that differs from the true covariate reliability. Obtaining unbiased results also depended on sample size. Our conclusion is that there is no additional benefit to using the EIV method over change score or ANCOVA methods for comparing the amount of change in pretest-posttest designs.