GESIS Training Courses
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Scientific Coordination

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

Administrative Coordination

Jacqueline Schüller
Tel: +49 0221 47694-160

Course 5: Advanced Survey Design

About
Location:
Cologne / Unter Sachsenhausen 6-8
 
Course duration:
Mo: 10:00-17:00 CEST
Tu-Fr: 9:00-16:00 CEST
General Topics:
Course Level:
Format:
Software used:
R and Stata
Duration:
Language:
Fees:
Students: 500 €
Academics: 750 €
Commercial: 1500 €
 
Keywords
Additional links
Lecturer(s): Bella Struminskaya, Angelo Moretti

About the lecturer - Bella Struminskaya

About the lecturer - Angelo Moretti

Course description

This course in 'advanced survey design' takes students beyond the introductory courses offered in BA and MA programs and will discuss current issues in one of the most important data collection methods: surveys. We focus on doing surveys in the Internet-era, the state of the art in both the design and the analysis of survey data. We discuss new ways to analyze modern surveys, including non-probability survey designs, surveys conducted via apps, and mixing surveys with Big Data such as augmenting survey data with auxiliary data (e.g., register data, digital trace data). The course combines 1-hour lectures with exercises on most of the topics discussed. The course is taught through lectures, group exercises as well as personal tutorial meetings that give participants the opportunity to discuss their own survey designs. Each day we will discuss a specific topic that each focuses on one or more aspects of survey design within the Total Survey Error framework. Course participants must be proficient working with a statistical software package (e.g., R, Stata, SPSS) at the level of at least knowing multiple linear regression. Most course materials are prepared for working with R.
 
A detailed syllabus with course times and literature will soon be available for download here.


Target group

The course will be interesting for PhD students or PhD candidates, postdocs, or advanced researchers with a background in a social science discipline or in Statistics, working on academic research projects. This course is focused on survey research within the academic (university/scientific institute) setting, as well as focused on current issues related to mobile surveys and Big Data.


Learning objectives

The aim of this course is to provide an overview of theory and practice of modern survey design and analysis, in particular focusing on modern methods of web surveys and the analysis of new types of data (e.g., sensor data). This course is useful for more experienced students.
 
By the end of the course participants will be ready to apply the learned methods and techniques towards their own surveys, are able to critically assess existing surveys and survey documentation and analyze survey data themselves successfully.
 
Organizational structure of the course
Lectures, exercises, group studies, tutoring sessions will be held daily between 10:00 and 17:00 on Monday, and the rest of the week between 9:00 and 16:00 including breaks.


Prerequisites

  • We expect students to have quite extensive knowledge of survey research (for example, by using survey data or conducting survey research in their daily work).
  • We expect students to have knowledge of statistics at the MSc level for social scientists (the general linear model).
  • We ask students to send us a brief motivation letter (up to 200 words), in which they write a short list of your experience with surveys and statistical analyses. Please include in the motivation letter what software you are proficient in, and what courses related to survey design you have taken.
  • Participants should be prepared to share information about the survey they are planning on conducting, they are currently involved with or would like to conduct in the future.
  •  
    Software and hardware requirements
    Participants need to bring a laptop computer to the course with their preferred statistical software installed. Since most exercises are prepared for R, ideally with R (https://cran.r-project.org/) and RStudio installed (https://www.rstudio.com/). Both programs are free and open source. Participants need to be able to download and install packages (internet access is provided by GESIS). Participants who wish to work in Stata but do not own a license, may request a short-term license valid for the duration of the course from GESIS Training.