Universität Wien FIND

200234 SE Advanced Seminar: Development and Education (2022S)

Practical advanced research methods using JASP

4.00 ECTS (2.00 SWS), SPL 20 - Psychologie
Continuous assessment of course work

Dieses Vertiefungsseminar kann für alle Schwerpunkte absolviert werden!

Vertiefungsseminare können nur für das Pflichtmodul B verwendet werden! Eine Verwendung für das Modul A4 Freie Fächer ist nicht möglich.


Note: The time of your registration within the registration period has no effect on the allocation of places (no first come, first served).


max. 20 participants
Language: English


Classes (iCal) - next class is marked with N

This course will be asynchronous. Videos will guide you through practical research methods in JASP, with voluntary weekly Q&A sessions where you can ask questions about specific methods.

The first session of 9 March 2022, at 09h45 is compulsary. All other sessions are voluntary sessions.

Wednesday 09.03. 09:45 - 11:15 Digital
Wednesday 16.03. 09:45 - 11:15 Digital
Wednesday 23.03. 09:45 - 11:15 Digital
Wednesday 30.03. 09:45 - 11:15 Digital
Wednesday 06.04. 09:45 - 11:15 Digital
Wednesday 27.04. 09:45 - 11:15 Digital
Wednesday 04.05. 09:45 - 11:15 Digital
Wednesday 11.05. 09:45 - 11:15 Digital
Wednesday 18.05. 09:45 - 11:15 Digital
Wednesday 25.05. 09:45 - 11:15 Digital
Wednesday 01.06. 09:45 - 11:15 Digital
Wednesday 08.06. 09:45 - 11:15 Digital
Wednesday 15.06. 09:45 - 11:15 Digital
Wednesday 22.06. 09:45 - 11:15 Digital
Wednesday 29.06. 09:45 - 11:15 Digital


Aims, contents and method of the course

This course is a gentle introduction to practical data analysis using JASP. We will be reviewing some basic methods such as correlations and regressions, as well as introducing some advanced methods such as structural equation models and measurement invariance testing. The course is aimed at developing a practical understanding and will allow students to master basic and advanced models by themselves.

The following will be covered within in the course:
• Correlation and Linear Regression
• Moderation and Mediation
• Path Analysis
• Confirmatory Factor Analysis
• Structural Equation Models
• Invariance

On all these topics, background information will be given, but the course focuses on hands-on examples. Further, opportunity to use own data sets and to discuss them in class will be given. Specifically, students will get an in-depth understanding of the underlying statistical model.

This course emphasizes open-source methods and data. As such we will be using only JASP and R to assess data and all of our datasets will be from open repositories of data.
No prior knowledge on latent modeling is needed, however, knowledge of basic statistic concepts (descriptive statistics, correlations, basic linear regression) is needed. We will also have a quick overview of these statistical concepts in the first few videos of the course.

**Please note that this course takes place in English**

Assessment and permitted materials

Grade Composition
• Quizzes and exercises (on Moodle) – 20%
• Essay – 60%
• Assignment – 20%

Minimum requirements and assessment criteria

Required Software: JASP, which can be downloaded here: https://jasp-stats.org/. If you have a MacBook and you experience difficulties downloading JASP, please consult this guide: https://jasp-stats.org/installation-guide/

Technology Requirements: You need to have a laptop or personal computer for this course. You also need internet access to view lessons, do quizzes on Moodle and submit your assignment. Please contact me if any of this may be a problem.

Practical Arrangements: Due to the uncertainty regarding the COVID-19 pandemic, the course will be offered virtually in the form of videos and quizzes on Moodle. There are dates by which you have to complete all course work, however this is a self-driven course. You are free to work through the course materials at any time from when they are posted on Moodle until 1 June 2022. Please note that the watching of lessons, completion of quizzes, and assignments on Moodle will all contribute to your final mark.

We will have weekly voluntary online Q&A sessions on Wednesdays at 09h45 to 11h15. These sessions are for you to pop in at any time during the time slots and ask any questions you may have on the material. These sessions are voluntary. The links for the zoom sessions will be posted on Moodle. In addition, you can email me at any time to ask questions.

Examination topics

1. Understand, practically implement, and interpret the results of the following statistical procedures:
a. Correlations
b. Linear regression
c. Moderation and mediation
d. Path analysis
e. Confirmatory factor analysis
f. Structural equation models (including syntax)
g. Measurement Invariance
2. Import, manage, and analyse datasets using JASP
3. Critically analyse structural equation model use and results in published peer-reviewed work

Reading list

Text Book: Kline, R. B. (2010). Principles and Practice of Structural Equation Modeling. This text is available in the library for you to reference or if you want additional information. It is not required for you to buy this book.

Association in the course directory

Last modified: Th 11.05.2023 11:27