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…

The RMC Research Corporation evaluation model C1--the special regression model (SRM)--was evaluated through a series of computer simulations and compared with an alternative model, the norm referenced model (NRM). Using local data and national norm data to determine reasonable values for sample size and pretest posttest correlation parameters, the…

The RMC Model A (norm-referenced) for evaluation of Title I programs is based upon the equipercentile assumption--that students maintain their percentile rank over a one-year period, provided that no special instrucional intervention is introduced. The control group, essentially the sample used to standardize the achievement test, represents the…

The regression-discontinuity approach to evaluating educational programs is reviewed, and regression-discontinuity post-program mean differences under various conditions are discussed. The regression-discontinuity design is used to determine whether post-program differences exist between an experimental program and a control group. The difference…