Researchers have become increasingly interested in programs' main and interaction effects of two variables (A and B, e.g., two treatment variables or one treatment variable and one moderator) on outcomes. A challenge for estimating main and interaction effects is to eliminate selection bias across A-by-B groups. I introduce Rubin's causal model to…

"Theory as Method: Small Theories of Treatments," by Mark W. Lipsey, is one of the most influential and highly cited articles to appear in "New Directions for Evaluation." It articulated an approach in which methods for studying causation depend, in large part, on what is known about the theory underlying the program. Lipsey discussed the benefits…

To predict suicide, explicit causal models of suicide outcome are needed in which predictors are temporally ordered and then tested statistically. Because suicide is a dichotomous, nominal scale outcome, only certain statistics for prediction are appropriate. Logistic regression, which utilizes the likelihood ratio test of statistical inference,…

Contrasts aptitude by treatment interaction (ATI) and hierarchical linear modeling (HLM) methods for making cross-level inferences between individual-level and group-level factors in school effectiveness research. Recommends HLM when intraclass correlations are high. ATI is suitable when intraclass correlations are low, but partitioning the…

Provides a brief overview of single-subject research designs. This method exercises its power by examining changes in single subjects' responses over time across experimental conditions. Describes a classroom project in which students collect repeated measures of their own behavior and graph the data. (MJP)