Universität Wien
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400018 SE Panel Data Analysis (2022S)

5.00 ECTS (2.00 SWS), SPL 40 - Doktoratsstudium Sozialwissenschaften
Continuous assessment of course work
Moodle

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).

Details

max. 15 participants
Language: English

Lecturers

Classes (iCal) - next class is marked with N

The course will be face-to-face or online, depending on the situation in May 2022.
In both cases, it is advised to install STATA on your computer/laptop (this is available from the University at student price https://zid.univie.ac.at/software-fuer-studierende/).
In case of an online course, please make sure to have a stable internet connection as well as webcam/microphone.

  • Wednesday 04.05. 10:00 - 14:00 C0628A Besprechung SoWi, NIG Universitätsstraße 7/Stg. III/6. Stock, 1010 Wien
  • Wednesday 11.05. 10:00 - 14:00 C0628A Besprechung SoWi, NIG Universitätsstraße 7/Stg. III/6. Stock, 1010 Wien
  • Wednesday 18.05. 10:00 - 14:00 C0628A Besprechung SoWi, NIG Universitätsstraße 7/Stg. III/6. Stock, 1010 Wien
  • Wednesday 25.05. 10:00 - 14:00 C0628A Besprechung SoWi, NIG Universitätsstraße 7/Stg. III/6. Stock, 1010 Wien
  • Wednesday 01.06. 10:00 - 14:00 C0628A Besprechung SoWi, NIG Universitätsstraße 7/Stg. III/6. Stock, 1010 Wien

Information

Aims, contents and method of the course

The module "Longitudinal data analysis" provides an introduction to the procedures for analysing longitudinal data. Starting with the basic idea of panel data analysis, we will discuss how to establish causal relationships. Real data examples will be shown, including how to prepare panel data, describe them and interpret the results from panel regressions. Both between and within estimations will be presented. Their advantages and disadvantages will be discussed.

Assessment and permitted materials

Minimum requirements and assessment criteria

Assessment criteria:
- Seminar paper using panel data analysis on a topic related to the PhD thesis (80%)
- Continuous assessment of class participation (20%)

Students need to achieve a pass grade (4) on each of the two assessment criteria

Examination topics

Reading list

The literature will be given in the first session.

Association in the course directory

Last modified: We 06.04.2022 15:10