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LDR | 03700nam 2200493 4500 | ||
001 | 0100798460▲ | ||
005 | 20240318154240▲ | ||
006 | m o d ▲ | ||
007 | cr#unu||||||||▲ | ||
008 | 240116s2023 us |||||||||||||||c||eng d▲ | ||
020 | ▼a9798380347648▲ | ||
035 | ▼a(MiAaPQ)AAI30686898▲ | ||
040 | ▼aMiAaPQ▼cMiAaPQ▲ | ||
082 | 0 | ▼a151▲ | |
100 | 1 | ▼aFossum, Jessica Louise.▲ | |
245 | 1 | 0 | ▼aImpacts of Model Specification on Statistical Power and Type I Error Rate in Moderated Mediation Analysis▼h[electronic resource]▲ |
260 | ▼a[S.l.]: ▼bUniversity of California, Los Angeles. ▼c2023▲ | ||
260 | 1 | ▼aAnn Arbor : ▼bProQuest Dissertations & Theses, ▼c2023▲ | |
300 | ▼a1 online resource(127 p.)▲ | ||
500 | ▼aSource: Dissertations Abstracts International, Volume: 85-03, Section: A.▲ | ||
500 | ▼aAdvisor: Montoya, Amanda K.▲ | ||
502 | 1 | ▼aThesis (Ph.D.)--University of California, Los Angeles, 2023.▲ | |
506 | ▼aThis item must not be sold to any third party vendors.▲ | ||
520 | ▼aModerated mediation models are used commonly in psychological research and other academic fields to model how and when effects occur. Researchers must choose which paths from the mediation model are moderated when specifying this type of model. This dissertation examines how model specification impacts statistical power and type I error rate for the index of moderated mediation. In a meta-analytic review, we found that six model specifications account for 85% of published moderated mediation analyses, so this dissertation focuses on those six models. When considering power and type I error rate, two attributes matter: the data analysis model, and the data generating process (DGP). In reference to the DGP, the data analysis model can either be correctly specified, over-specified, underspecified, or completely misspecified. A Monte Carlo simulation study was run to examine the impacts of model specification on power and type I error rate, and results were analyzed using multi-level logistic regression along with figures and tables. Over-specified models had lower statistical power to detect a significant index of moderated mediation compared to correctly specified models. Under-specified models had slightly higher power when moderation on the direct effect was omitted, but otherwise, under-specified models had much lower power than correctly specified models. Parameter bias was also unacceptably high for most under-specified models. Completely misspecified models generally still had acceptable type I error rates, with a notable exception of inflated type I error rates where moderation was omitted from the direct effect. Overall, while many published moderated mediation models may not have large enough sample sizes for adequate statistical power, over-specifying or under-specifying models can lead to lower statistical power as well, while complete model misspecification risks an inflated type I error rate.▲ | ||
590 | ▼aSchool code: 0031.▲ | ||
650 | 4 | ▼aQuantitative psychology.▲ | |
650 | 4 | ▼aPsychology.▲ | |
650 | 4 | ▼aTherapy.▲ | |
653 | ▼aModerated mediation▲ | ||
653 | ▼aStatistical power▲ | ||
653 | ▼aData generating process▲ | ||
653 | ▼aData analysis model▲ | ||
690 | ▼a0632▲ | ||
690 | ▼a0621▲ | ||
690 | ▼a0212▲ | ||
710 | 2 | 0 | ▼aUniversity of California, Los Angeles.▼bPsychology 0780.▲ |
773 | 0 | ▼tDissertations Abstracts International▼g85-03A.▲ | |
773 | ▼tDissertation Abstract International▲ | ||
790 | ▼a0031▲ | ||
791 | ▼aPh.D.▲ | ||
792 | ▼a2023▲ | ||
793 | ▼aEnglish▲ | ||
856 | 4 | 0 | ▼uhttp://www.riss.kr/pdu/ddodLink.do?id=T16935264▼nKERIS▼z이 자료의 원문은 한국교육학술정보원에서 제공합니다.▲ |
Impacts of Model Specification on Statistical Power and Type I Error Rate in Moderated Mediation Analysis[electronic resource]
Document Type
국외eBook
Title
Impacts of Model Specification on Statistical Power and Type I Error Rate in Moderated Mediation Analysis [electronic resource]
Author
Corporate Name
Publication
[S.l.] : University of California, Los Angeles. 2023 Ann Arbor : ProQuest Dissertations & Theses , 2023
Physical Description
1 online resource(127 p.)
General Note
Source: Dissertations Abstracts International, Volume: 85-03, Section: A.
Advisor: Montoya, Amanda K.
Advisor: Montoya, Amanda K.
Dissertation Note
Thesis (Ph.D.)--University of California, Los Angeles, 2023.
Summary Note
Moderated mediation models are used commonly in psychological research and other academic fields to model how and when effects occur. Researchers must choose which paths from the mediation model are moderated when specifying this type of model. This dissertation examines how model specification impacts statistical power and type I error rate for the index of moderated mediation. In a meta-analytic review, we found that six model specifications account for 85% of published moderated mediation analyses, so this dissertation focuses on those six models. When considering power and type I error rate, two attributes matter: the data analysis model, and the data generating process (DGP). In reference to the DGP, the data analysis model can either be correctly specified, over-specified, underspecified, or completely misspecified. A Monte Carlo simulation study was run to examine the impacts of model specification on power and type I error rate, and results were analyzed using multi-level logistic regression along with figures and tables. Over-specified models had lower statistical power to detect a significant index of moderated mediation compared to correctly specified models. Under-specified models had slightly higher power when moderation on the direct effect was omitted, but otherwise, under-specified models had much lower power than correctly specified models. Parameter bias was also unacceptably high for most under-specified models. Completely misspecified models generally still had acceptable type I error rates, with a notable exception of inflated type I error rates where moderation was omitted from the direct effect. Overall, while many published moderated mediation models may not have large enough sample sizes for adequate statistical power, over-specifying or under-specifying models can lead to lower statistical power as well, while complete model misspecification risks an inflated type I error rate.
Subject
ISBN
9798380347648
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