Customer Reviews

Quasi-Experimentation: Design & Analysis Issues for Field Settings

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"Quasi-Experimentation" carries on the work begun by Campbell and Stanley in "Experimental and Quasi-Experimental Designs for Research." Beginning with a discussion of the positivist origins of science and evaluation research, it details a range of quasi-experimental approaches suitable to "real world" research, together with statistical techniques applicable to each. The book includes a realistic assessment of the barriers to randomization in natural settings, including the observation that true randomization is rarely used unless there is a marked power differential between the researcher and the subjects. The book is thoughtful, well-written, and invaluable.

This is a "must-have" book for anyone engaged in field research or a student of field research methods. The approach is to maximize validity of research findings based on a number of considerations in the design of field research. Examines the pit-falls made by most new and inexperienced field researchers and evaluators. Before you conduct your next program evaluation, design an applied research study, or start to collect dissertation data, read this book!

I grant that it's not the most up-to-date, transparent, visually stimulating, or artfully written book. Even so, it's very rewarding for a reader who's serious about expanding his/her toolkit and gaining a more professional grasp of challenging issues in research design--experimental, non experimental, or quasi-experimental. Material on threats to validity, especially, continues to be cited extremely widely. Their discussion of time series modelling is intriguing, and they offer a particularly thought-provoking section on the intricacies of analyzing gain scores and the choice of ANOVA vs. ANCOVA.

Although this book is from 1979, and would appear to be replaced by the recent book Shadish, Cook, and Campbell, _Experimental and Quasi-Experimental Designs_ (2002), it is actually not redundant with the newer book as it explains a number of issues clearly that are omitted in SCC.