Survey Sampling and Weighting

About

This practical course will cover the process of probability sampling and weighting for (social science) survey data. This includes a) sampling techniques, b) methods of weighting survey data, including design weighting, nonresponse weighting, and adjustment weighting, and c) methods of parameter estimation for complex sample survey data. Please note that the course will only provide a short excursus to non-probability sampling.

The course is more applied than theoretical, but you are expected to be comfortable with statistics and have some experience with survey data analysis. For each topic, you will do exercises in Stata to apply the techniques learned in the lectures. Prior knowledge and experience in how to use Stata for survey data analysis is needed. R-scripts with solutions to the exercises will be made available as well (but not discussed in more detail)

Course leader

Simon Kühne, Bielefeld University

Target group

You will find the course useful if:
- you have experience conducting surveys and/or analyzing survey data but have no experience with survey sampling and weighting,
- you are planning your own survey data collection and need to sample and/or weight the data

Course aim

By the end of the course, you will:
- know about the most commonly used sample designs, including stratified sampling, cluster sampling, and multi-stage sampling,
- know how to create design weights, nonresponse weights, and apply adjustment weighting techniques,
- know how the sample design can affect data analysis and how to incorporate complex survey designs and survey weights into parameter estimatio

Fee info

The rates include the tuition fee, course materials, the academic program, social and plenary program, and coffee/tea breaks