Explaining the fundamentals of mediation and moderation analysis, this engaging book also shows how to integrate the two using an innovative strategy known as conditional process analysis. Procedures are described for testing hypotheses about the mechanisms by which causal effects operate, the conditions under which they occur, and the moderation of mechanisms. Relying on the principles of ordinary least squares regression, Andrew Hayes carefully explains the estimation and interpretation of direct and indirect effects, probing and visualization of interactions, and testing of questions about moderated mediation. Examples using data from published studies illustrate how to conduct and report the analyses described in the book. Of special value, the book introduces and documents PROCESS, a macro for SPSS and SAS that does all the computations described in the book. The companion website (www.afhayes.com) offers free downloads of PROCESS plus data files for the book's examples. Unique features include: *Compelling examples (presumed media influence, sex discrimination in the workplace, and more) with real data; boxes with SAS, SPSS, and PROCESS code; and loads of tips, including how to report mediation, moderation and conditional process analyses. *Appendix that presents documentation on use and features of PROCESS. *Online supplement providing data, code, and syntax for the book's examples.
... 131 Gunn, R. L., 131 Gunther, A., xv. Gunther, A. C., 86 Gurmen, M. S., 150 GvirSman, S. D., xiv, 11,397 Haase, A. M., 188 Hahl, O., 188 Halliwell, E., 532 Hamer, M., 530 Hamilton, L. C., 9 Hammond, S. I., 117 Han, Z. Author Index 671.
Includes all testable terms, concepts, persons, places, and events. Just the FACTS101 provides the essentials of the textbook: all of the outlines, highlights, and quizzes for your textbook with optional online comprehensive practice tests.
"Written in a friendly, conversational style, this book offers a hands-on approach to statistical mediation and moderation for both beginning researchers and those familiar with modeling.
Concepts, Applications, and Implementation Richard B. Darlington, Andrew F. Hayes. Correlations X1 X2 X3 X4 X5 X6 X7 X8 X9 X10 X1 Pearson Correlation Sig. (2-tailed) N X2 Pearson Correlation Sig. (2-tailed) N X3 Pearson Correlation Sig.
Wright showed that the path coefficient for a mediating process was the product of all the path coefficients in a chain of mediation. ... an idea popularized by Pearson in his classic book, The Grammar of Science (Pearson, 1911).
Andrew F. Hayes ... be negative because D > C. As with Pearson's r and Spearman's r, the closer to gamma is to 1 (in absolute value), the stronger the association. ... These are very close to Pearson's r, but this won't always be true.
Explores even the fundamental assumptions underlying mediation analysis
Lauded for its easy-to-understand, conversational discussion of the fundamentals of mediation, moderation, and conditional process analysis, this book has been fully revised with 50% new content, including sections on working with ...
A must-have volume for every communication researcher's library, The SAGE Sourcebook of Advanced Data Analysis Methods for Communication Research provides an introductory treatment of various advanced statistical methods applied to research ...
example, than to travel to twenty different schools to obtain data from one student at each. In ... However, formulas for calculating standard errors that are incorporated into most statistical packages are based on an SRS design where ...