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

Richard E Zinbarg*, Satoru Suzuki, Amanda A. Uliaszek, Alison R. Lewis

*Corresponding author for this work

Research output: Contribution to journalArticle

33 Scopus citations

Abstract

Miller and Chapman (2001) argued that 1 major class of misuse of analysis of covariance (ANCOVA) or its 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.

Original languageEnglish (US)
Pages (from-to)307-319
Number of pages13
JournalJournal of Abnormal Psychology
Volume119
Issue number2
DOIs
StatePublished - Jan 1 2010

Keywords

  • Analysis of covariance
  • Analysis of partial variance
  • Bias
  • Structural equation modeling

ASJC Scopus subject areas

  • Psychiatry and Mental health
  • Biological Psychiatry

Fingerprint Dive into the research topics of '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'. Together they form a unique fingerprint.

  • Cite this