What are the two main reasons for including covariates in ANOVA?
A)1.) To increase within-group error variance and 2.To reduce between-group error variance
B)1.) To reduce within-group error variance and 2.) Elimination of confounds
C)1.) To increase within-group error variance and 2).To correct the means for the covariate
D)1.) 1.To increase between-group variance and 2.) To reduce within-group error variance

Question

Quizplus · Accepted Answer

The main reasons for including covariates in ANOVA are to reduce within-group error variance (by accounting for variability in the dependent variable that is related to the covariate) and to eliminate confounding variables that may affect the relationship between the independent and dependent variables. Including a covariate can also help to increase statistical power by reducing error variance, but this is not one of the primary reasons for including covariates in ANOVA. Finally, covariates are not used to correct the means of the dependent variable, but rather to control for the effects of other variables on the dependent variable.

What Are the Two Main Reasons for Including Covariates in ANOVA