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Introduction to mediation, moderation, and conditional process analysis : a regression-based approach / Andrew F. Hayes.

By: Material type: TextTextSeries: Methodology in the social sciencesPublication details: New York : The Guilford Press, 2022.Edition: Third editionDescription: xx, 732 pages : illustrarions ; 26 cmISBN:
  • 9781462549030
Subject(s): DDC classification:
  • 001.4/22 23
LOC classification:
  • HA31.3 .H39 2022
Summary: "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 multicategorical antecedent variables, the use of PROCESS version 3 for SPSS and SAS for model estimation, and annotated PROCESS v3 outputs. Using the principles of ordinary least squares regression, Andrew F. Hayes carefully explains procedures for testing hypotheses about the conditions under and the mechanisms by which causal effects operate, as well as the moderation of such mechanisms. Hayes shows how to estimate and interpret direct, indirect, and conditional effects; probe and visualize interactions; test questions about moderated mediation; and report different types of analyses. Data for all the examples are available on the companion website ([ital]www.afhayes.com[/ital]), along with links to download PROCESS"--
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Holdings
Item type Current library Collection Call number Vol info Status Date due Barcode
Main Long Main Long Martin Oduor-Otieno Library This item is located on the library first floor Non-fiction HA31.3 .H39 2022 (Browse shelf(Opens below)) 30556/22 Available MOOL22080081

Includes bibliographical references and index.

"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 multicategorical antecedent variables, the use of PROCESS version 3 for SPSS and SAS for model estimation, and annotated PROCESS v3 outputs. Using the principles of ordinary least squares regression, Andrew F. Hayes carefully explains procedures for testing hypotheses about the conditions under and the mechanisms by which causal effects operate, as well as the moderation of such mechanisms. Hayes shows how to estimate and interpret direct, indirect, and conditional effects; probe and visualize interactions; test questions about moderated mediation; and report different types of analyses. Data for all the examples are available on the companion website ([ital]www.afhayes.com[/ital]), along with links to download PROCESS"--

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