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Structural Equation Modeling: A Multidisciplinary Journal Volume 28, 2021 - Issue 5
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Research Article

Investigating the Impact of Covariate Inclusion on Sample Size Requirements of Factor Mixture Modeling: A Monte Carlo Simulation Study

Yan Wanga University of Massachusetts LowellCorrespondence[email protected]
ORCID Iconhttps://orcid.org/0000-0003-2237-8816
ORCID Icon,
Hsien-Yuan Hsua University of Massachusetts LowellORCID Iconhttps://orcid.org/0000-0003-2155-2093
ORCID Icon &
Eunsook Kimb University of South FloridaORCID Iconhttps://orcid.org/0000-0003-1054-1735
ORCID Icon
Pages 716-724 | Published online: 12 May 2021

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Read on this site (1)

Eunsook Kim, Diep Nguyen, Siyu Liu & Yan Wang. (2022) Mixed Effects of Item Parceling on Performance of Factor Mixture Modeling. Structural Equation Modeling: A Multidisciplinary Journal 29:2, pages 207-217.
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Articles from other publishers (4)

Li Ping, Song Xiaosong & Li Jinzhao. (2022) Research on farmers’ households credit behavior and social capital acquisition. Frontiers in Psychology 13.
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Samantha F. Anderson. (2021) Power(ful) myths: misconceptions regarding sample size in quality of life research. Quality of Life Research 31:10, pages 2917-2929.
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Yan Wang, Chunhua Cao & Eunsook Kim. (2022) Covariate inclusion in factor mixture modeling: Evaluating one-step and three-step approaches under model misspecification and overfitting. Behavior Research Methods.
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James B. Schreiber. 2022. Contemporary Research Methods in Pharmacy and Health Services. Contemporary Research Methods in Pharmacy and Health Services 601 616 .

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