Using the errors-in-variables method in two-group pretest-posttest design.

dc.contributor.authorCounsell, Alyssa
dc.contributor.authorCribbie, Robert
dc.date.accessioned2017-06-26T12:35:40Z
dc.date.available2017-06-26T12:35:40Z
dc.date.issued2017
dc.description.abstractCulpepper 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.en_US
dc.identifier.citationCounsell, A., & Cribbie, R. A. (2017). Using the errors-in-variables method in two-group pretest-posttest design. Methodology, 13(1), 1-8. http://dx.doi.org/10.1027/1614-2241/a000122
dc.identifier.urihttp://hdl.handle.net/10315/33236
dc.language.isoenen_US
dc.publisherMethodologyen_US
dc.rights.journalhttps://us.hogrefe.com/products/journals/methodologyen_US
dc.titleUsing the errors-in-variables method in two-group pretest-posttest design.
dc.typeArticleen_US

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