GESIS Training Courses
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Scientific Coordination

Dr.
Sebastian E. Wenz
Tel: +49 221 47694-159

Administrative Coordination

Angelika Ruf
Tel: +49 221 47694-162

Course 6: Survey Sampling and Weighting

Lecturer(s):
Dr. Simon Kühne, Jannes Jacobsen

Date: 17.08 - 21.08.2020 ics-file

Location: Online via Zoom

About the lecturer - Dr. Simon Kühne

About the lecturer - Jannes Jacobsen

Course description

[This is a 30 hour class.]
This practical course will cover the process of survey sampling, weighting and estimation. This includes a) methods of sample selection, b) methods of weighting including design weighting, nonresponse weighting and poststratification techniques, and c) methods of parameter estimation for complex sample 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. Prior knowledge in how to use Stata is recommended.
A detailed syllabus for this course is available for download here.


Keywords



Target group

Participants will find the course useful if:
  • they have experience conducting surveys and/or analyzing survey data but have no experience with survey sampling and weighting.
  • they plan their own survey data collection and need to sample and/or weight the data.


Learning objectives

By the end of the course participants will:
  • know about the most commonly used sample designs including, clustered sampling, stratified sampling, and multi-stage sampling.
  • know how to create design weights, nonresponse weights and apply poststratification techniques.
  • know how the sample design can affect data analysis and how to incorporate complex survey designs and survey weights into parameter estimation.
 
Organizational Structure of the Course:  
This is a five-day course with a total amount of 30 hours of virtual class time. Participants can expect a mix of interactive teaching, exercises, and opportunity for individual consultation. Exercises (most of them in Stata, some examples in R) are designed to deepen their understanding of the course material.
 


Prerequisites

  • Introductory course in statistics. No prior knowledge of sampling theory is assumed.
  • Prior knowledge in Stata is required for this course.
  • Basic understanding in survey methodology and how to handle survey data.
  •  
     
    Software and Hardware Requirements:
    Participants who do not own a copy of Stata will be provided with access to a full Stata licence by GESIS for the duration of the course. Stata will be installed and activated prior to the course by GESIS staff through remote access on the participants' machines.  
     
    Participants who own a copy of Stata should install the following Stata ados prior to the course: gsample, unique, distinct, survwgt, fre, coefplot, moremata, estout.
    Participants who also wish to use R should have a recent version of R (https://cran.r-project.org/) and Rstudio installed (https://www.rstudio.com/). Both programs are free and open source.


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