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Introduction to mediation, moderation, and conditional process analysis : a regression-based approach ; Series editor's by Todd D. Little

By: Hayes, Andrew F
Material type: BookSeries: Publisher: New York : Guilford Publications, c2018.Edition: 2nd ed.Description: xx, 692 p. : ill. ; 27 cm.ISBN: 9781462534654Subject(s): Social sciences -- Statistical methods | Mediation (Statistics) | Regression analysisDDC classification: 001.422 HA IN Online resources: Access electronically | Location Map
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 (www.afhayes.com), along with links to download PROCESS.
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Item type Home library Call number Status Notes Date due Barcode Item holds
REGULAR University of Wollongong in Dubai
Main Collection
001.422 HA IN (Browse shelf) Checked out May2018 03/27/2024 T0059864
Total holds: 0

Description based upon print version of record.

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 (www.afhayes.com), along with links to download PROCESS.

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