By integrating and translating the current methodological and statistical work into a practical guide, the authors of this text provide readers with a state-of-the-art introduction to the various approaches to doing meta-analysis.

By integrating and translating the current methodological and statistical work into a practical guide, the authors of this text provide readers with a state-of-the-art introduction to the various approaches to doing meta-analysis.

Whether in the laboratory or while doing fieldwork, 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.

In this volume Lipsey examines the concept of design sensitivity and explains statistical power and the elements that determine it. Through careful explanations and selection of examples he explores a variety of topics: factors that degrade design sensitivity, effect size parameters and approaches to assessing it, how to estimate statistical power for various statistical tests, and the special problems statistical power poses for treatment effectiveness research. This book is a vital resource for evaluators, methodologists, statisticians, psychologists, public health professionals and educators.

By integrating and translating the current methodological and statistical work into a practical guide, the authors of this text provide readers with a state-of-the-art introduction to the various approaches to doing meta-analysis.

By integrating and translating the current methodological and statistical work into a practical guide, the authors of this text provide readers with a state-of-the-art introduction to the various approaches to doing meta-analysis.

Whether in the laboratory or while doing fieldwork, 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.

In this volume Lipsey examines the concept of design sensitivity and explains statistical power and the elements that determine it. Through careful explanations and selection of examples he explores a variety of topics: factors that degrade design sensitivity, effect size parameters and approaches to assessing it, how to estimate statistical power for various statistical tests, and the special problems statistical power poses for treatment effectiveness research. This book is a vital resource for evaluators, methodologists, statisticians, psychologists, public health professionals and educators.