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540008 SE Research Seminar (2022S)
Multivariate and Complex Data Analysis for Psychological Science
Continuous assessment of course work
Labels
Registration/Deregistration
Note: The time of your registration within the registration period has no effect on the allocation of places (no first come, first served).
- Registration is open from Th 10.03.2022 13:15 to Sa 12.03.2022 13:11
- Deregistration possible until Sa 12.03.2022 13:11
Details
Language: German, English
Lecturers
Classes (iCal) - next class is marked with N
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.- Wednesday 09.03. 11:30 - 13:00 Hörsaal C Psychologie, NIG 6.Stock A0618
- Wednesday 16.03. 11:30 - 13:00 Hörsaal C Psychologie, NIG 6.Stock A0618
- Wednesday 23.03. 11:30 - 13:00 Hörsaal C Psychologie, NIG 6.Stock A0618
- Wednesday 30.03. 11:30 - 13:00 Hörsaal C Psychologie, NIG 6.Stock A0618
- Wednesday 06.04. 11:30 - 13:00 Hörsaal C Psychologie, NIG 6.Stock A0618
- Wednesday 27.04. 11:30 - 13:00 Hörsaal C Psychologie, NIG 6.Stock A0618
- Wednesday 04.05. 11:30 - 13:00 Hörsaal C Psychologie, NIG 6.Stock A0618
- Wednesday 11.05. 11:30 - 13:00 Hörsaal C Psychologie, NIG 6.Stock A0618
- Wednesday 18.05. 11:30 - 13:00 Hörsaal C Psychologie, NIG 6.Stock A0618
- Wednesday 25.05. 11:30 - 13:00 Hörsaal C Psychologie, NIG 6.Stock A0618
- Wednesday 01.06. 11:30 - 13:00 Hörsaal C Psychologie, NIG 6.Stock A0618
- Wednesday 08.06. 11:30 - 13:00 Hörsaal C Psychologie, NIG 6.Stock A0618
- Wednesday 15.06. 11:30 - 13:00 Hörsaal C Psychologie, NIG 6.Stock A0618
- Wednesday 22.06. 11:30 - 13:00 Hörsaal C Psychologie, NIG 6.Stock A0618
Information
Aims, contents and method of the course
Assessment and permitted materials
Presentations and active participation, peer feedback.
Minimum requirements and assessment criteria
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.
Examination topics
Presentations, discussions, peer feedback
Reading list
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.
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.
Association in the course directory
Last modified: Th 10.03.2022 13:30
- 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.