Design Sensitivity: Statistical Power for Experimental Research / Edition 1 available in Paperback
All researchers face an important challenge - designing research that will have sufficient sensitivity to detect those effects it purports to investigate. Sample size, validity and sensitivity, experimental error, subject variability, and the type of statistical analysis all influence the sensitivity of a research design. Through careful explanations and selection of examples, Lipsey examines the concept of design sensitivity and explains statistical power and the elements that determine it.
|Edition description:||New Edition|
|Product dimensions:||6.00(w) x 1.25(h) x 9.00(d)|
About the Author
Mark W. Lipsey is the Director of the Center for Evaluation Research and Methodology, and a Senior Research Associate, at the Vanderbilt Institute for Public Policy Studies (Ph.D. in Psychology from The Johns Hopkins University in 1972). His professional interests are in the areas of public policy, program evaluation research, social intervention, field research methodology, and research synthesis (meta-analysis). The topics of his recent research have been risk and intervention for juvenile delinquency and substance use, early childhood education programs, and issues of methodological quality in program evaluation research. Professor Lipsey serves on the editorial boards of Evaluation and Program Planning, Psychological Bulletin, the Journal of Experimental Criminology, and the American Journal of Community Psychology, and boards or committees of, among others, the National Research Council, the Department of Education What Works Clearinghouse, Campbell Collaboration, and Blueprints for Violence Prevention. He is a recipient of the American Evaluation Association’s Paul Lazarsfeld Award, the Society of Prevention Research’s Nan Tobler Award, a Fellow of the American Psychological Society, and co-author of the program evaluation textbook, Evaluation: A Systematic Approach and the meta-analysis primer, Practical Meta-Analysis.
Table of ContentsPART ONE: STATISTICAL POWER IN TREATMENT EFFECTIVENESS RESEARCHTreatment Effectiveness Research and Design SensitivityThe Statistical Power FrameworkEffect Size The Problematic ParameterHow to Estimate Statistical PowerPART TWO: USEFUL APPROACHES AND TECHNIQUESDependent MeasuresDesign, Sample Size, and AlphaThe Independent Variable and the Role of TheoryPutting It All Together