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Introduction to latent variable modeling under cross-sectional design using Mplus



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1Introduction to latent variable modeling under cross-sectional design using Mplus Psiquiatria e Psicologia Médica 02/03/2020 a
27/04/2020
Inscrição:
22/01/2020 a 01/03/2020
Período:
02/03/2020 a 27/04/2020
Responsável:
Prof. Dr. Hugo Cogo-Moreira
Créditos:
2
Resumo:
The course will be taught in English and it is focused on hands-on data analysis using Mplus.

Código:
-
Programa:
33009015032P3 Psiquiatria e Psicologia Médica
Co-responsável:
Sareh Panjeh and Juliana Valente
Local:
LOGO ABAIXO
Dias e horários:
Segundas-feiras das 9horas até 12horas
Vagas:
25
Créditos:
2
Critérios de ingresso:
Graduate Students with interest in quantitative methods. The course assumes an intermediary knowledge in biostatistics/data modeling (t-test, ANOVA, linear and logistic regressions). No previous knowledge on Mplus (https://www.statmodel.com/) is required.
Carga horária teórica:
15
Carga horária prática:
15
Carga horária total:
30
Ementa/Programação:
1) Measurement model specification & fit indices, 2) Confirmatory factor analysis (unidimensional models)/Item Response Theory with 1, 2, 3, and 4 parameters, 3) Confirmatory factor analysis (multidimensional models) and nested models testing under different estimators, 4) Bifactor models and Subscale reliability and viability – new advances under S-1 approach, 5) Invariance testing (multigroup confirmatory factor analysis, multiple indicators multiple causes approach, moderated nonlinear factor analysis, 6) Alignment and Partial invariance testing, 7) Multimethod and Multitrait models: separating methodological effects from trait effects, 8) Bayesian confirmatory factor analysis, 9) Monte Carlo Simulation for sample size estimation Evaluation: Homework (50%) and during the course two tests will be conducted for evaluation (50%). LOCAIS: Ed. Manoel Lopes - Nader Wafae (NW) - 56 lugares 02/03/2020 09:00 02/03/2020 12:00 Pós-Graduação em Psiquiatria - Introduction to latent variable modeling under cross-sectional design using Mplus Ed. Octávio de Carvalho - Nylceo Marques de Castro (Anf. C) - 85 lugares 09/03/2020 09:00 09/03/2020 12:00 Pós-Graduação em Psiquiatria - Introduction to latent variable modeling under cross-sectional design using Mplus Ed. de Anfiteatros - Álvaro Guimarães Filho (AGF) - 61 lugares - 1° andar 16/03/2020 09:00 16/03/2020 12:00 Pós-Graduação em Psiquiatria - Introduction to latent variable modeling under cross-sectional design using Mplus Ed. Octávio de Carvalho - Nylceo Marques de Castro (Anf. C) - 85 lugares 23/03/2020 09:00 23/03/2020 12:00 Pós-Graduação em Psiquiatria - Introduction to latent variable modeling under cross-sectional design using Mplus Ed. de Anfiteatros - Álvaro Guimarães Filho (AGF) - 61 lugares - 1° andar 30/03/2020 09:00 30/03/2020 12:00 Pós-Graduação em Psiquiatria - Introduction to latent variable modeling under cross-sectional design using Mplus Ed. de Anfiteatros - Álvaro Guimarães Filho (AGF) - 61 lugares - 1° andar 06/04/2020 09:00 06/04/2020 12:00 Pós-Graduação em Psiquiatria - Introduction to latent variable modeling under cross-sectional design using Mplus Ed. de Anfiteatros - Álvaro Guimarães Filho (AGF) - 61 lugares - 1° andar 13/04/2020 09:00 13/04/2020 12:00 Pós-Graduação em Psiquiatria - Introduction to latent variable modeling under cross-sectional design using Mplus Ponte de feriado 20/04/2020 00:00 Ed. de Anfiteatros - Álvaro Guimarães Filho (AGF) - 61 lugares - 1° andar 27/04/2020 09:00 27/04/2020 12:00 Pós-Graduação em Psiquiatria - Introduction to latent variable modeling under cross-sectional design using Mplus
Referências:
Program Class 1 (Ed. Manoel Lopes - Nader Wafae (NW)) Recommended Reading: BROWN, T. A. (2015) Confirmatory factor analysis for applied research. 2nd ed. NY: Guilford. (Chapter 1, 2, and 3) Class 2 (Ed. Octávio de Carvalho - Nylceo Marques de Castro (Anf. C)) Recommended Reading: BANDALOS, D (2018). Measurement Theory and Applications for Social Sciences. Chapter 13 and 14 MUTHÉN, L. K. & MUTHÉN, B.O. (2013). Mplus user’s guide. 7th ed. Los Angeles, CA: Muthen & Muthen. Models example 5.2 and 5.5. Class 3 (Ed. de Anfiteatros - Álvaro Guimarães Filho (AGF) Recommended Reading: MUTHÉN, L. K. & MUTHÉN, B.O. (2013). Mplus user’s guide. 7th ed. Los Angeles, CA: Muthen & Muthen. Models example 5.1, 5.6 Gignac, G. E. (2005). Revisiting the factor structure of the WAIS-R: Insights through nested factor modeling. Assessment, 12(3), 320-329. Class 4 (Ed. Octávio de Carvalho - Nylceo Marques de Castro) Recommended Reading Reise, S. P. (2012). The rediscovery of bifactor measurement models. Multivariate behavioral research, 47(5), 667-696. Eid, M., Geiser, C., Koch, T., & Heene, M. (2017). Anomalous results in G-factor models: Explanations and alternatives. Psychological Methods, 22(3), 541. Class 5 (Ed. de Anfiteatros - Álvaro Guimarães Filho (AGF)) Recommended Reading Van de Schoot, R., Lugtig, P., & Hox, J. (2012). A checklist for testing measurement invariance. European Journal of Developmental Psychology, 9(4), 486-492. Bauer, D. J. (2017). A more general model for testing measurement invariance and differential item functioning. Psychological methods, 22(3), 507. Extra reading Class 6 (Ed. de Anfiteatros - Álvaro Guimarães Filho (AGF) Recommended Reading Muthén, B. & Asparouhov T. (2014). IRT studies of many groups: The alignment method. Frontiers in Psychology, Volume 5, DOI: 10.3389/fpsyg.2014.00978 Byrne, B. M., Shavelson, R. J. and Muthén, B. O. 1989. Testing for equivalence of factor covariance and mean structures: The issue of partial measurement invariance. Psychological Bulletin, 105: 456–466. Class 7 (Ed. de Anfiteatros - Álvaro Guimarães Filho (AGF) Recommended Reading Eid, M., Lischetzke, T., & Nussbeck, F. W. (2006). Structural equation models for multitrait-multimethod data. Eid, M., Lischetzke, T., Nussbeck, F. W., & Trierweiler, L. I. (2003). Separating trait effects from trait-specific method effects in multitrait-multimethod models: A multiple-indicator CT-C (M-1) model. Psychological methods, 8(1), 38. Class 8 Recommended Reading Muthén, B., & Asparouhov, T. (2012). Bayesian structural equation modeling: a more flexible representation of substantive theory. Psychological methods, 17(3), 313. Class 9 Wolf, E. J., Harrington, K. M., Clark, S. L., & Miller, M. W. (2013). Sample Size Requirements for Structural Equation Models: An Evaluation of Power, Bias, and Solution Propriety. Educational and Psychological Measurement, 73(6), 913–934. https://doi.org/10.1177/0013164413495237
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Inscrição:
http://www.psiquiatriaunifesp.posgrad.com.br/
E-mail:
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Telefone:
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