This paper discusses four criteria for selecting covariates when utilizing the analysis of covariance in quasiexperimental research: completeness, causation, independence, and fallibility. Completeness is the extent to which the known or suspected sources of bias are accounted for by covariates used in an experiment. Causation is the requirement that covariates used in nonrandom research designs are causally related to the dependent variable of a study. Independence is the requirement that there is no treatment/covariate interaction. Fallibility refers to the reliability of the covariate measure. Ways of determining to what degree these criteria are met are suggested. (Author)