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Analysis of Covariance

  1. Tenko Raykov

Published Online: 30 JAN 2010

DOI: 10.1002/9780470479216.corpsy0053

Corsini Encyclopedia of Psychology

Corsini Encyclopedia of Psychology

How to Cite

Raykov, T. 2010. Analysis of Covariance. Corsini Encyclopedia of Psychology. 1–2.

Author Information

  1. Michigan State University

Publication History

  1. Published Online: 30 JAN 2010

Abstract

Analysis of covariance (ANCOVA) is a statistical method that may be viewed as an extension of analysis of variance (ANOVA) when, in addition to one or more factors (discrete explanatory variables, typically group membership), it is required to account for possible differences due to a continuous variable(s), usually called covariate(s) or concomitant variable(s). The latter variable(s) co-varies with a dependent variable under consideration (response, outcome), and it is of interest to examine whether group differences on the latter may be related to group differences on the covariate(s). Typically, a covariate is highly correlated with a response variable; that is, the covariate contains information about the response variable and therefore possibly also about group differences on the outcome measure(s). Empirical settings in which ANCOVA is appropriate usually have at least one categorical factor and one or more continuous covariates.

Keywords:

  • statistics;
  • multivariate statistics