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Basic longitudinal analysis
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Basic longitudinal analysis

Informacje ogólne

Kod przedmiotu: WF-PS-VECCHBASIC-ER Kod Erasmus / ISCED: 14.4 / (brak danych)
Nazwa przedmiotu: Basic longitudinal analysis
Jednostka: Instytut Psychologii
Grupy: Grupa przedmiotów - oferta Erasmus
Punkty ECTS i inne: 8.00
Język prowadzenia: angielski
Poziom przedmiotu: zaawansowany
Symbol/Symbole efektów kształcenia: K_W02
K_W03
K_K03
Skrócony opis:

This is an introductory, applied course on the analysis of longitudinal data. The course aims to provide students basic understanding of statistical methods for studying stability and change with longitudinal data. It includes practical work with computer software (Mplus) and real data.

Pełny opis:

This is an introductory, applied course on the analysis of longitudinal data. The course aims to provide students basic understanding of statistical methods for studying stability and change with longitudinal data. It includes practical work with computer software (Mplus) and real data.

Basic principles in the analysis of change with repeated measures. Different types of stability and change: rank-order stability, mean-level change, ipsative stability. Students will use the Mplus software to fit different statistical approaches for the analysis of change (e.g., autoregressive models), with a special focus on latent growth curve modeling (LGM).

Literatura:

- Stoolmiller, M. (1994). Antisocial behavior, delinquent peer association and unsupervised wandering for boys: Growth and change from childhood to early adolescence. Multivariate Behavioral Research, 29, 263-288.

- Duncan, S.C., & Duncan, T.E. (1996). A Multivariate Latent Growth Curve Analysis of Adolescent Substance Use. Structural Equation Modeling: A Multidisciplinary Journal, 3, 323-347.

- Muthen, B. O., & Khoo, S.-T. (1998). Longitudinal studies of achievement growth using latent variable modeling. Learning and Individual Differences, 10, 73-101.

- Curran, P.J. (2000). A latent curve framework for studying developmental trajectories of adolescent substance use. In J. Rose, L. Chassin, C. Presson, & J. Sherman (Eds.), Multivariate Applications in Substance Use Research, (pp. 1-42). Hillsdale, NJ: Erlbaum.

- Little, T.D., Bovaird, J.A., & Slegers, D.W. (2006). Methods for the analysis of change. In D.K. Mroczek & T.D. Little (Eds.), Handbook of personality development (pp. 181-211). Mahwah, NJ, USA: LEA.

- Curran, P.J., Obeidat, K., & Losardo, D. (2010). Twelve frequently asked questions about growth curve modeling. Journal of Cognition and Development, 11, 121‐136.

Metody i kryteria oceniania:

Students are required to replicate the results of a published manuscript using Mplus, writing a short research report (up to three pages), interpreting and commenting the data.

Zajęcia w cyklu "Semestr letni 2017/18" (jeszcze nie rozpoczęty)

Okres: 2018-02-01 - 2018-06-30
Wybrany podział planu:


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Typ zajęć: Wykład, 30 godzin, 20 miejsc więcej informacji
Koordynatorzy: Agnieszka Szymańska, Adam Świeżyński, Michele Vecchione
Prowadzący grup: Agnieszka Szymańska, Adam Świeżyński, Michele Vecchione
Lista studentów: (nie masz dostępu)
Zaliczenie: Egzaminacyjny
E-Learning: E-Learning (pełny kurs) z podziałem na grupy
Typ przedmiotu: fakultatywny dowolnego wyboru
Skrócony opis:

This is an introductory, applied course on the analysis of longitudinal data. The course aims to provide students basic understanding of statistical methods for studying stability and change with longitudinal data. It includes practical work with computer software (Mplus) and real data.

Pełny opis:

This is an introductory, applied course on the analysis of longitudinal data. The course aims to provide students basic understanding of statistical methods for studying stability and change with longitudinal data. It includes practical work with computer software (Mplus) and real data.

Basic principles in the analysis of change with repeated measures. Different types of stability and change: rank-order stability, mean-level change, ipsative stability. Students will use the Mplus software to fit different statistical approaches for the analysis of change (e.g., autoregressive models), with a special focus on latent growth curve modeling (LGM).

Literatura:

- Stoolmiller, M. (1994). Antisocial behavior, delinquent peer association and unsupervised wandering for boys: Growth and change from childhood to early adolescence. Multivariate Behavioral Research, 29, 263-288.

- Duncan, S.C., & Duncan, T.E. (1996). A Multivariate Latent Growth Curve Analysis of Adolescent Substance Use. Structural Equation Modeling: A Multidisciplinary Journal, 3, 323-347.

- Muthen, B. O., & Khoo, S.-T. (1998). Longitudinal studies of achievement growth using latent variable modeling. Learning and Individual Differences, 10, 73-101.

- Curran, P.J. (2000). A latent curve framework for studying developmental trajectories of adolescent substance use. In J. Rose, L. Chassin, C. Presson, & J. Sherman (Eds.), Multivariate Applications in Substance Use Research, (pp. 1-42). Hillsdale, NJ: Erlbaum.

- Little, T.D., Bovaird, J.A., & Slegers, D.W. (2006). Methods for the analysis of change. In D.K. Mroczek & T.D. Little (Eds.), Handbook of personality development (pp. 181-211). Mahwah, NJ, USA: LEA.

- Curran, P.J., Obeidat, K., & Losardo, D. (2010). Twelve frequently asked questions about growth curve modeling. Journal of Cognition and Development, 11, 121‐136.

Opisy przedmiotów w USOS i USOSweb są chronione prawem autorskim.
Właścicielem praw autorskich jest Uniwersytet Kardynała Stefana Wyszyńskiego w Warszawie.