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020			_a9781000905984
020			_z9781032202860(PRINT)
035			_a(ALMA)991001138557505936
040			_aSEK _erda _beng _cTUPM
041			_aund
050			_aQA 278 _bN49 2024
100	1		_aNewsom, Jason T.
245	1	0	_aLongitudinal Structural Equation Modeling : A Comprehensive Introduction / _cJason T. Newsom
250			_aSecond edition
264			_bNew York, _aRoutledge, _cc2024.
300			_axx, 501 pages : _billustrations (black and white) ; _c26 cm.
336			_2rdacontent
337			_2rdamedia
338			_2rdacarrier
504			_aIncludes bibliographic references and index.
505			_aContentsList of FiguresList of TablesPreface to the Second EditonPreface to the First EditionAcknowledgementsExample Data SetsChapter 1. Review of Some Key Latent Variable PrinciplesChapter 2. Longitudinal Measurement InvarianceChapter 3. Structural Models for Comparing Dependent Means and Proportions Chapter 4. Fundamental Concepts of Stability and Change Chapter 5. Cross-Lagged Panel ModelsChapter 6. Latent State-Trait ModelsChapter 7. Linear Latent Growth Curve Models Chapter 8. Nonlinear Latent Growth Curve ModelsChapter 9. Nonlinear Latent Growth Curve ModelsChapter 10. Latent Class and Latent TransitionChapter 11. Growth Mixture Models Chapter 12. Intensive Longitudinal Models: Time Series and Dynamic Structural Equation Models Chapter 13. Survival Analysis Models Chapter 14. Missing Data and Attrition Appendix A: Notation Appendix B: Why Does the Single Occasion Scaling Constraint Approach Work? Appendix C: A Primer on the Calculus of ChangeGlossaryIndex
520			_a"Longitudinal Structural Equation Modeling is a comprehensive resource that reviews structural equation modeling (SEM) strategies for longitudinal data to help readers determine which modeling options are available for which hypotheses. This accessibly written book explores a range of models, from basic to sophisticated, including the statistical and conceptual underpinnings that are the building blocks of the analyses. By exploring connections between models, it demonstrates how SEM is related to other longitudinal data techniques and shows when to choose one analysis over another. Newsom emphasizes concepts and practical guidance for applied research rather than focusing on mathematical proofs, and new terms are highlighted and defined in the glossary. Figures are included for every model along with detailed discussions of model specification and implementation issues and each chapter also includes examples of each model type, descriptions of model extensions, comment sections that provide practical guidance, and recommended readings. Expanded with new and updated material, this edition includes many recent developments, a new chapter on growth mixture modeling, and new examples. Ideal for graduate courses on longitudinal (data) analysis, advanced SEM, longitudinal SEM, and/or advanced data (quantitative) analysis taught in the behavioral, social, and health sciences, this new edition will continue to appeal to researchers in these fields." _b-- Back cover
590			_aNewsom, J. T. (2023). Longitudinal structural equation modeling: A comprehensive introduction (2nd ed.). Routledge.
650			_aStructural equation modeling
650			_aLongitudinal studies
650			_aMultivariate analysis
776	0	8	_iPrint _tLongitudinal Structural Equation Modeling : A Comprehensive Introduction / Jason T. Newsom. _z9781032202860
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