12 August 2022
Introduction to Survey Design
This course gives an overview of the design and implementation of surveys from the initial planning phase to the data preparation as a final step. Topics include survey mode assessment and selection, sampling frames and designs, nonresponse, questionnaire design, cognitive pretesting, assessing measurement errors and data editing. The course is taught from a Total Survey Error perspective weighing data quality at each step of the process against associated costs.
The course is taught through formal lectures in which the theoretical foundation in the literature is discussed, less formal presentations and discussions of survey design in existing survey research, as well as personal tutorial meetings that give participants the opportunity to discuss exercises and 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. First, the choice of the survey mode is discussed, and how different ways to sample respondents follow from that choice. On the second day, we focus on the issue of survey nonresponse - how to prevent, analyze, and correct for it. On the third and fourth day, the actual survey content is discussed - how to write survey questions, make sure that they measure what they are intended to measure, test them, and finally, how to assess whether survey data are of good quality. On the final day, we focus on data coding and maximizing quality. We conclude with an overview perspective of all survey errors and their interaction with survey costs.
The course will be applicable to surveys of individuals, households, and organizations in different survey modes: mail, face-to-face, web, and paper-and-pencil surveys.
Dr. Bella Struminskaya is an assistant professor in methods and statistics at Utrecht University. Dr. Peter Lugtig is an associate professor at the Department of Methodology and Statistics at Utrecht University, The Netherlands.
Participants will find the course useful if they:
- are thinking about conducting a quantitative survey themselves;
- use survey data and wish to understand its potential errors;
- are Master or PhD students preparing their own survey;
- are researchers who collaborate within a survey research project.
The course is tailored to those relatively new to the area of survey methodology possibly planning to later follow more advanced and specialized courses at the GESIS Summer School. The course does not provide an introduction into data analysis of survey data. Rather, it is focused on the design of surveys.
- no previous experience in survey research is needed; however, some practical experience in conducting surveys and analyzing data will be beneficial;
- a basic understanding of statistics is assumed, at the level of basic inferential statistics (t-tests);
- all students need to send a brief summary of their experience with surveys (about 0.5 page) and the questions they have about how to design surveys before the start of the course to the instructors, at the latest on August 2, 2019.
This course does not include the use of statistical software.
By the end of the course participants will:
- have a good grasp of the complexities of interacting survey errors;
- be able to design a survey project themselves taking these into account;
- be prepared for more specialized courses at the GESIS Summer School.
- Certificate of attendance issued upon completion.
- 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 70).
EUR 500: Student/PhD student rate.
EUR 750: Academic/non-profit rate.
The rates include the tuition fee, course materials, the academic program, access to library and IT facilities, and coffee/tea breaks.
Scholarships are available from the German Academic Exchange Service (DAAD) and the European Survey Research Association (ESRA).