Catalog
LDR | 03110nam 2200493 4500 | ||
001 | 0100801187▲ | ||
005 | 20240325092835▲ | ||
006 | m o d ▲ | ||
007 | cr#unu||||||||▲ | ||
008 | 240116s2023 us |||||||||||||||c||eng d▲ | ||
020 | ▼a9798380595117▲ | ||
035 | ▼a(MiAaPQ)AAI30788269▲ | ||
040 | ▼aMiAaPQ▼cMiAaPQ▲ | ||
082 | 0 | ▼a151▲ | |
100 | 1 | ▼aCoutts, Jacob Joseph.▲ | |
245 | 1 | 0 | ▼aEnhancing the Specification, Testing, and Interpretation of Conditional Indirect Effects▼h[electronic resource]▲ |
260 | ▼a[S.l.]: ▼bThe Ohio State University. ▼c2023▲ | ||
260 | 1 | ▼aAnn Arbor : ▼bProQuest Dissertations & Theses, ▼c2023▲ | |
300 | ▼a1 online resource(136 p.)▲ | ||
500 | ▼aSource: Dissertations Abstracts International, Volume: 85-04, Section: B.▲ | ||
500 | ▼aAdvisor: Pek, Jolynn.▲ | ||
502 | 1 | ▼aThesis (Ph.D.)--The Ohio State University, 2023.▲ | |
506 | ▼aThis item must not be sold to any third party vendors.▲ | ||
520 | ▼aResearchers interested in understanding causal relationships must not only test if X causes Y, but how and/or when X causes Y. Mediation analysis is a tool that allows researchers to identify the mechanism(s) by which one variable causes another, whereas moderation analysis allows researchers to detect when one variable's effect is heterogenous across levels of another variable (or multiple variables). Although these analyses lead to a deeper understanding of an observed relationship, they are still often too simplistic in isolation to properly model real-world effects. Combining mediation and moderation into a single analysis allows one to study conditional indirect effects-that is, when an indirect effect of X on Y is variable across the levels of a moderator.Methodological researchers have paid much attention on how to test for conditional indirect effects. However, considerably less work has been devoted to evaluating the performance of these proposed methods or interpreting the results of these tests. A review of the simulation studies that have been done reveals that current testing methods have relatively poor performance except for the most optimistic combinations of effect and sample size. Despite this, many substantive researchers continue to use these methods and rely on them for dichotomous decisions about and interpretations of such effects.▲ | ||
590 | ▼aSchool code: 0168.▲ | ||
650 | 4 | ▼aQuantitative psychology.▲ | |
650 | 4 | ▼aBehavioral psychology.▲ | |
650 | 4 | ▼aSocial psychology.▲ | |
653 | ▼aMediation analysis▲ | ||
653 | ▼aModeration analysis▲ | ||
653 | ▼aConditional indirect effects▲ | ||
653 | ▼aConditional process analysis▲ | ||
690 | ▼a0632▲ | ||
690 | ▼a0451▲ | ||
690 | ▼a0384▲ | ||
710 | 2 | 0 | ▼aThe Ohio State University.▼bPsychology.▲ |
773 | 0 | ▼tDissertations Abstracts International▼g85-04B.▲ | |
773 | ▼tDissertation Abstract International▲ | ||
790 | ▼a0168▲ | ||
791 | ▼aPh.D.▲ | ||
792 | ▼a2023▲ | ||
793 | ▼aEnglish▲ | ||
856 | 4 | 0 | ▼uhttp://www.riss.kr/pdu/ddodLink.do?id=T16935759▼nKERIS▼z이 자료의 원문은 한국교육학술정보원에서 제공합니다.▲ |
Enhancing the Specification, Testing, and Interpretation of Conditional Indirect Effects[electronic resource]
Document Type
국외eBook
Title
Enhancing the Specification, Testing, and Interpretation of Conditional Indirect Effects [electronic resource]
Author
Corporate Name
Publication
[S.l.] : The Ohio State University. 2023 Ann Arbor : ProQuest Dissertations & Theses , 2023
Physical Description
1 online resource(136 p.)
General Note
Source: Dissertations Abstracts International, Volume: 85-04, Section: B.
Advisor: Pek, Jolynn.
Advisor: Pek, Jolynn.
Dissertation Note
Thesis (Ph.D.)--The Ohio State University, 2023.
Summary Note
Researchers interested in understanding causal relationships must not only test if X causes Y, but how and/or when X causes Y. Mediation analysis is a tool that allows researchers to identify the mechanism(s) by which one variable causes another, whereas moderation analysis allows researchers to detect when one variable's effect is heterogenous across levels of another variable (or multiple variables). Although these analyses lead to a deeper understanding of an observed relationship, they are still often too simplistic in isolation to properly model real-world effects. Combining mediation and moderation into a single analysis allows one to study conditional indirect effects-that is, when an indirect effect of X on Y is variable across the levels of a moderator.Methodological researchers have paid much attention on how to test for conditional indirect effects. However, considerably less work has been devoted to evaluating the performance of these proposed methods or interpreting the results of these tests. A review of the simulation studies that have been done reveals that current testing methods have relatively poor performance except for the most optimistic combinations of effect and sample size. Despite this, many substantive researchers continue to use these methods and rely on them for dichotomous decisions about and interpretations of such effects.
Subject
ISBN
9798380595117
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