Modeling the process by which participants are selected into groups, rather than adjusting for preexisting group differences, provides the basis for several new approaches to the analysis of data from nonrandomized studies. Econometric approaches, the propensity scores approach, and the relative assignment variable approach to the modeling of…

Causal models often omit variables that should be included, use variables that are measured fallibly, and ignore time lags. Such practices can lead to severely biased estimates of effects. The discussion explains these biases and shows how to take them into account. (Author)

The adequacy of traditional effect size measures for research synthesis is challenged. Analogues to analysis of variance and multiple regression analysis for effect sizes are presented. The importance of tests for the consistency of effect sizes in interpreting results, and problems in obtaining well-specified models for meta-analysis are…

Evaluation is discussed as an information-gathering process. Currently popular evaluation programs are reviewed in relation to decision making and various approaches that seem to contribute to the decision utility of evaluation (e.g. classical approaches, Bayesian approaches, adaptive designs, and model-based evaluations) are described. (Author/AL)

Seven essays on efforts of evaluate prevention programs aimed at the acquired immune deficiency syndrome (AIDS) are presented. Topics include public health psychology, mathematical models of epidemiology, estimates of incubation periods, ethnographic evaluations of AIDS prevention programs, an AIDS education model, theory-based evaluation, and…