24 August 2018
Sampling, Weighting, and Estimation
This course will cover: methods of sample selection; calculation of weights that adjust for nonresponse and undercoverage; and analysis of complex survey data. We will also discuss analysis of nonprobability surveys. 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. Students will get the most out of the class if they have prior experience with Stata.
Stephanie Eckman, PhD, is a Fellow at RTI International in Washington DC where she designs samples and consults on all aspects of survey design. From 2010 to 2015 she was a senior researcher at the Institute for Employment Research in Nuremberg, Germany.
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;
- they 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 the first week);
- Experience in handling survey data is helpful but not necessary.
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 300: Student/PhD student rate.
EUR 450: Academic/non-profit rate.
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.
5 ESRA scholarships are available for participation in one main course.