What statistical procedure is used to control for extraneous variables while comparing group means?

The correct answer, ANCOVA, is particularly effective for controlling for extraneous variables when comparing the means across groups. ANCOVA, or Analysis of Covariance, combines ANOVA and regression. It allows researchers to assess the main and interaction effects of categorical and continuous independent variables on a dependent variable, while statistically controlling for the influence of one or more continuous covariates. This helps ensure that any observed differences between group means can more accurately be attributed to the independent variable rather than confounding factors.

For instance, if you are examining the effect of a therapy program on depression scores while knowing that age significantly influences these scores, ANCOVA enables you to adjust the depression scores based on age before comparing groups. This adjustment helps in isolating the effect of the independent variable on the dependent variable, thus providing a clearer understanding of the relationship.

The other methods listed serve different purposes: regression analysis focuses on predicting the value of a variable based on others but may not compare group means directly. MANOVA compares multiple dependent variables but does not control for extraneous variables like ANCOVA does. The t-test compares means between two groups without any covariate adjustments and is less suitable in situations where confounding variables are present.