Biased parameter estimates and inflated type I error rates in analysis of covariance (and analysis of partial variance) arising from unreliability: Alternatives and remedial strategies.

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Abstract
Miller and Chapman (2001) argued that 1 major class of misuse of analysis of covariance (ANCOVA) or Os multiple regression counterpart, analysis of partial variance (APV), arises from attempts to use an ANCOVA/APV to answer a research question that is not meaningful in the 1st place. Unfortunately, there is another misuse of ANCOVAs/APVs that arises frequently in psychopathology studies even when addressing consensually meaningful research questions. This misuse arises from inflated Type I error rates: in ANCOVA/APV inferential tests of the unique association of the independent variable with the dependent variable when the covariate and independent variables are correlated and measured with error. Alternatives to conventional ANCOVAs/APVs are discussed, as are steps that can be taken to minimize the impact of this bias on drawing valid inferences when conventional ANCOVAs/APVs are used.
Funding Information
  • Northwestern University
  • National Institutes of Health (R01-MH65652-01, R01-EY014110; R01-EY018197)
  • National Science Foundation (BCS0643191)

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