26 August 2016
Sampling, Weighting and Estimation
This course will cover: methods of sample selection; creation of analysis weights that adjust for nonresponse and undercoverage; and analysis of complex survey data. The emphasis of the course is more applied than theoretical, but students are expected to be comfortable with statistics and to have some experience with data analysis. For each topic, students will do exercises in Stata that apply the techniques learned in the lectures.
You can find the full syllabus of the course with complete information on the topics, literature, and day-to-day schedule on https://training.gesis.org.
Stephanie Eckman, PhD is Senior Survey Research Methodologist at RTI International in Washington DC, USA.
Participants will find the course useful if they:
- have some experience conducting surveys and/or analyzing social science data, but have not yet studied sampling;
- are conducting their own survey or are analyzing survey data.
- Introductory course in statistics. No prior knowledge of sampling theory is assumed, but students should be comfortable with statistical concepts such as hypothesis testing, variance, standard errors, confidence intervals, etc.;
- Prior knowledge of Stata is required for this course;
- Basic understanding of survey methodology (this could be gained in the course "Introduction to Survey Design" in week 1);
- Experience in handling survey data is helpful.
By the end of the course participants will:
- have a sound understanding of the most frequently used sample designs (one- and two-stage sampling, clustered sampling; stratified sampling, and related designs);
- know how to create probability weights, and have experience with several methods for adjusting such weights for nonresponse and undercoverage;
- understand how and why the design of a sample survey affects the analysis of the data;
- know the appropriate methods to use in Stata to analyze complex survey data, and the pros and cons of each method.
- Certificate of attendance issued upon completion.
- 2 ECTS points via the University of Mannheim for regular attendance and satisfactory work on daily assignments (EUR 20).
- 4 ECTS points via the University of Mannheim for regular attendance and satisfactory work on daily assignments and for submitting a paper/report of about 5000 words to the lecturer(s) up to 4 weeks after the end of the summer school (EUR 50).
EUR 250: Student/PhD student rate.
EUR 350: Academic/non-profit rate.
Early bird discount: EUR 50 for applicants who book and pay by April 30.
The rates include the tuition fee, course materials, the academic program, access to library and IT facilities, coffee/tea, and a number of social activities.
10 DAAD scholarships are available via the Center for Doctoral Studies in Social and Behavioral Sciences (CDSS) at the University of Mannheim.