<unk> <unk>  is a general linear model with one continuous explanatory variable and one or more factors.<unk>  is a merger of<unk>  and regression for continuous variables.<unk>  tests whether certain factors have an effect after removing the variance for which quantitative predictors (covariates) account. The inclusion of covariates can increase statistical power because it accounts for some of the variability.
Analysis of covariance
Linear regression
Analysis of variance
Analysis of rhythmic variance
Likelihood-ratio test
Chi-square test
Kendall tau rank correlation coefficient
Box plot