Contents
Are covariates the same as independent variables?
Similar to an independent variable, a covariate is complementary to the dependent, or response, variable. A variable is a covariate if it is related to the dependent variable. This may be the reason that in regression analyses, independent variables (i.e., the regressors) are sometimes called covariates.
Can a covariate be dichotomous?
Yes, you may use a categorical covariate. However, if it has more than two levels, you will need to re-express the categories into C – 1 dummy variates (where C is the number of categories you have in your data set). If only two levels, then coding them as “1” and “2”, respectively, will work just fine.
Can you use a categorical variable as a covariate?
Now, you can put a categorical variable into Covariates, as long as it’s coded properly–dummy or effect coding are common.
When do you use the term covariate in an analysis?
The most precise definition is its use in Analysis of Covariance, a type of General Linear Model in which the independent variables of interest are categorical, but you also need to adjust for the effect of an observed, continuous variable–the covariate.
Is the covariate always continuous or a control variable?
In this context, the covariate is always continuous, always a control variable, and always observed (i.e. observations weren’t randomly assigned its values, you just measured what was there).
Is the covariate always the key independent variable?
In this context, the covariate is always continuous, never the key independent variable, and always observed (i.e. observations weren’t randomly assigned its values, you just measured what was there).
What happens when you add a covariate to an ANOVA?
While the inclusion of a covariate into an ANOVA generally increases statistical power by accounting for some of the variance in the dependent variable and thus increasing the ratio of variance explained by the independent variables, adding a covariate into ANOVA also reduces the degrees of freedom.