Universität Wien

540008 SE Forschungsseminar (2022S)

Multivariate and Complex Data Analysis for Psychological Science

4.00 ECTS (2.00 SWS), SPL 54 - Doktoratsstudium Psychologie und Biologie mit Schwerpunkt CoBeNe
Prüfungsimmanente Lehrveranstaltung
Moodle

An/Abmeldung

Hinweis: Ihr Anmeldezeitpunkt innerhalb der Frist hat keine Auswirkungen auf die Platzvergabe (kein "first come, first served").

Details

Sprache: Deutsch, Englisch

Lehrende

Termine (iCal) - nächster Termin ist mit N markiert

Update on 08.03.2022: The seminar will be conducted on site, as planned.

The seminar will be conducted on site. Depending on the current situation of the pandemic or applicable regulations, a switch to digital teaching could be possible.

  • Mittwoch 09.03. 11:30 - 13:00 Hörsaal C Psychologie, NIG 6.Stock A0618
  • Mittwoch 16.03. 11:30 - 13:00 Hörsaal C Psychologie, NIG 6.Stock A0618
  • Mittwoch 23.03. 11:30 - 13:00 Hörsaal C Psychologie, NIG 6.Stock A0618
  • Mittwoch 30.03. 11:30 - 13:00 Hörsaal C Psychologie, NIG 6.Stock A0618
  • Mittwoch 06.04. 11:30 - 13:00 Hörsaal C Psychologie, NIG 6.Stock A0618
  • Mittwoch 27.04. 11:30 - 13:00 Hörsaal C Psychologie, NIG 6.Stock A0618
  • Mittwoch 04.05. 11:30 - 13:00 Hörsaal C Psychologie, NIG 6.Stock A0618
  • Mittwoch 11.05. 11:30 - 13:00 Hörsaal C Psychologie, NIG 6.Stock A0618
  • Mittwoch 18.05. 11:30 - 13:00 Hörsaal C Psychologie, NIG 6.Stock A0618
  • Mittwoch 25.05. 11:30 - 13:00 Hörsaal C Psychologie, NIG 6.Stock A0618
  • Mittwoch 01.06. 11:30 - 13:00 Hörsaal C Psychologie, NIG 6.Stock A0618
  • Mittwoch 08.06. 11:30 - 13:00 Hörsaal C Psychologie, NIG 6.Stock A0618
  • Mittwoch 15.06. 11:30 - 13:00 Hörsaal C Psychologie, NIG 6.Stock A0618
  • Mittwoch 22.06. 11:30 - 13:00 Hörsaal C Psychologie, NIG 6.Stock A0618

Information

Ziele, Inhalte und Methode der Lehrveranstaltung

Guided by the students’ individual research interests and needs, this seminar offers guidance and assistance in the application of multivariate and complex statistical models (cross-sectional and longitudinal) in psychology. The seminar specifically covers:
- Structural equation modeling (SEM; with continuous latent variables)
- Path analysis
- Mediation and moderation analysis
- Confirmatory factor analysis
- Multi-group modeling
- Multilevel modeling
- Growth curve modeling
- Latent class analysis (LCA; with categorical latent variables)
- Latent profile analysis (LPA; with categorical latent variables)

Students present their research questions and analytical strategy. In class, we will deal with the nature, assumptions, and requirements of the various statistical analyses and models as needed; data formats (e.g., wide vs. long) and data management; and computational issues (e.g., regarding estimators). Data analysis with the free open-source software R (e.g., package lavaan), Mplus, and SPSS/JASP, where applicable, will be explained and discussed. Some prior experience with R is recommended, but not mandatory.

Course enrollment: via personal email to ulrich.tran@univie.ac.at.

The seminar will be held either in German or English, depending on the language requirements of participating students.

Art der Leistungskontrolle und erlaubte Hilfsmittel

Presentations and active participation, peer feedback.

Mindestanforderungen und Beurteilungsmaßstab

All students present their research questions and analytic strategy to provide input for the seminar (oral presentation + short exposé [max. 2 pages]). All students provide peer feedback to the other students' presentations.

The presentation and active participation are equally weighted for grading.

Prüfungsstoff

Presentations, discussions, peer feedback

Literatur

Guided by the students' research interests and needs, e.g.:
Brown, V. A. (2021). An introduction to linear mixed-effects modeling in R. Advances in Methods and Practices in Psychological Science, 4(1), 1-19. https://doi.org/10.1177/2515245920960351
Finch, W. H., Boley, J. E., & Kelley, K. (2019). Multilevel modeling using Mplus (2nd ed.). CRC Press.
Gana, K., & Broc, G. (2019). Structural equation modeling with lavaan. Wiley.
Kline, R. B. (2016). Principles and practice of structural equation modeling (4th ed.). Guilford.
Rosseel, Y. (n.d.). The lavaan project. http://lavaan.ugent.be
Wang, J., & Wang, X. (2020). Structural equation modeling: Applications using Mplus. Wiley.

Zuordnung im Vorlesungsverzeichnis

Letzte Änderung: Do 10.03.2022 13:30