Analysis of Covariance

Mini, K G (2023) Analysis of Covariance. In: Training Manual on Statistical Designs and Analytical Methods for Multifactor Experiments. ICAR- Central Marine Fisheries Research Institute, Kochi, pp. 66-71.

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Abstract

The analysis of covariance (ANCOVA) is a statistical technique used to examine differences between three or more groups while using a continuous variable termed as covariate as a control variable between the groups. ANCOVA, model the response of a variable as a linear function of predictors, with the coefficients of the line varying among different groups. The advantages of incorporating the covariates are typically (1) to explain variation on the dependent variable and (2) to reduce error variation. These adjustments result in more interpretable effects, narrower confidence intervals, and an increase in the statistical power of the analysis. Thus, it differs from the analysis of variance (ANOVA) which is used to determine whether differences among test samples might be caused by random variation. ANCOVA is a general linear model that blends ANOVA and the linear regression.

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