What is the analysis of covariance (ANCOVA)?

The analysis of covariance (ANCOVA) is a statistical technique that combines ANOVA (analysis of variance) and linear regression. The technique analyzes grouped data that consists of at least one categorical independent variable called the factor and one or more interval-natured independent variables called covariates. The covariate performs the task of removing the extraneous variation from the dependent variable. This is important as the effects of the factors are of major concern in an ANCOVA test.  

ANCOVA can be used as an extension of analysis of variance (ANOVA) or as an extension of multiple regression to compare multiple regression lines. It can tell analysts what additional information they can obtain by considering one factor (independent variable) at a time, without the influence of others. For example, in a study to determine if a new drug is effective for depression, an ANOVA test can indicate whether or not the treatment is effective. Using ANCOVA, analysts can control for other factors such as family life, employment or drug use, which may influence the outcome.