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Instructors: Cristóbal Moya
Event type:
Seminar / exercise
Org-unit: Sociology, Politics & Economics
Displayed in timetable as:
Advanced Methods | F
Hours per week:
1,5
Credits:
3,0
Location:
Campus der Zeppelin Universität
Language of instruction:
Englisch
Min. | Max. participants:
10 | 20
Priority scheme: Standard-Priorisierung
Course content:
The course is focused in the analysis of real-world survey data considering the complex sampling designs that commonly are involved in their data generating processes. Statistical software and courses commonly assume that survey data were drawn from a simple random sample of the target population, although this is rarely the case. This course provides an introduction to procedures developed for the analysis of complex sample survey data. The emphasis is on the applied analysis using the R software environment.
Educational objective:
This course has two specific aims: 1) to introduce students to the estimation and statistical inference with survey data from complex sampling designs; 2) to foster data analysis skills with real-world survey data based on complex sampling designs.
Further information about the exams:
The course evaluation consists of the following components:
a. Homeworks (30%)
b. Data analysis project (15%)
c. Paper draft (15%)
d. Project report (40%)
Mandatory literature:
- Agresti, A. (2018). Statistical methods for the social sciences (Fifth edition). Pearson.
- Heeringa, S. G., West, B. T., & Berglund, P. A. (2010). Applied Survey Data Analysis. CRC Press.
- Lohr, S. L. (2009). Sampling: Design and Analysis. Cengage Learning.
- Lumley, T. (2010). Complex Surveys: A Guide to Analysis Using R. Wiley.
- Lumley, T. (2020). survey: Analysis of Complex Survey Samples (4.0) [computer software]. https://CRAN.R-project.org/package=survey
- R Core Team. (2020). R: A language and environment for statistical computing. https://www.R-project.org/
- Valliant, R., Dever, J. A., & Kreuter, F. (2018). Practical Tools for Designing and Weighting Survey Samples. Springer.
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