Conducting Meta-Analysis Using SAS reviews the meta-analysis statistical procedure and shows the reader how to conduct one using SAS. It presents and illustrates the use of the PROC MEANS procedure in SAS to perform the data computations called for by the two most commonly used meta-analytic procedures, the Hunter & Schmidt and Glassian approaches.
This book serves as both an operational guide and user's manual by describing and explaining the meta-analysis procedures and then presenting the appropriate SAS program code for computing the pertinent statistics. The practical, step-by-step instructions quickly prepare the reader to conduct a meta-analysis. Sample programs available on the Web further aid the reader in understanding the material.
Intended for researchers, students, instructors, and practitioners interested in conducting a meta-analysis, the presentation of both formulas and their associated SAS program code keeps the reader and user in touch with technical aspects of the meta-analysis process. The book is also appropriate for advanced courses in meta-analysis psychology, education, management, and other applied social and health sciences departments.
"The authors have done a good job compiling a set of instructions that might encourage some researchers to successfully complete a reasonable empirical study in place of a more traditional qualitative literature review. The book presents a well-researched look at successful applications."
—Journal of the American Statistical Association
"…a 'must have' for a researcher or professional interested in writing his or her own program for conducting meta-analysis."
University of Akron
Contents: Preface. The Theory of Meta-Analysis--Sampling Error and the Law of Small Numbers. Meta-Analysis of Effect Sizes. Meta-Analysis of Correlations. Outliers in Meta-Analytic Data. Summary and Guidelines for Implementing a Meta-Analysis. Appendices: Reference and Information Sources for the Behavioral and Social Sciences. Equation for Computing the Pooled Within-Group Standard Deviation. Conversion and Transformation Equations. Upper Percentage Points for the Chi-Square Distribution.
This series of books offers highly accessible and widely applicable methodological topics that have broad appeal and are written in easy-to understand language. Sponsored by the Society of Multivariate Experimental Psychology http://www.smep.org/, it welcomes methodological applications from a variety of disciplines, such as psychology, public health, sociology, education, and business. Authored or edited volumes should feature one of several approaches:
Interested persons should e-mail: Lisa L. Harlow at LHarlow@uri.edu.