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182   $cc$2rdamedia
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200 10$aStructural equation modeling $eapplications using Mplus /$fJichuan Wang, Xiaoqian Wang
205   $aSecond edition.
210  1$aHoboken, New Jersey ;$aChichester, West Sussex, England :$cWiley,$d[2020]
210  4$d©2020
215   $a1 online resource (537 pages)
225 0 $aWiley series in probability and statistics
311   $a1-119-42270-1 
320   $aIncludes bibliographical references and index.
327   $aConfirmatory factor analysis -- Structural equation model -- Latent growth models (LGM) for longitudinal data analysis -- Multi-group modeling -- Mixture modeling -- Sample size for structural equation modeling.
330   $aDiscusses and demonstrates various SEM models using both cross-sectional and longitudinal data with both continuous and categorical outcomes. Explores different methods for sample size estimate and statistical power analysis for SEM. By following the examples provided in this second edition, readers will be able to build their own SEM models using Mplus. Teachers, graduate students, and researchers in social sciences and health studies will also benefit from this book"--$cProvided by publisher
606   $aStructural equation modeling$xData processing
606   $aMultivariate analysis$xData processing
606   $aSocial sciences$xStatistical methods$xData processing
615  0$aStructural equation modeling$xData processing.
615  0$aMultivariate analysis$xData processing.
615  0$aSocial sciences$xStatistical methods$xData processing.
676   $a300.285
700   $aWang$b Jichuan$0960180
702   $aWang$b Xiaoqian
801  0$bMiAaPQ
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