Cologne, Germany

Factorial Survey Design

when 15 August 2022 - 19 August 2022
language English
duration 1 week
credits 4 EC
fee EUR 500

The factorial survey design (“vignette analysis”) is a method that integrates multi-factorial experimental set-ups into surveys. Respondents are asked to evaluate hypothetical situations, objects, or persons. By systematically varying attributes of the descriptions, it is possible to determine their influence on respondents' stated attitudes, decisions, or choices. The experimental variation of the stimuli makes it possible to estimate the influence of each attribute on the evaluation. The factorial survey method is therefore an appropriate instrument for testing theoretical predictions. Moreover, because the experiment is embedded in a survey questionnaire, it is possible to reach heterogeneous sample populations.

This course provides a theoretical and practical overview of factorial survey methods. Participants will gain practical insights into all the single steps necessary to design a factorial survey experiment: (1) construction of vignettes, (2) selection of an experimental design, (3) drafting and programming of questionnaires (for online surveys as well as paper and pencil surveys), (4) data management, and (5) data analysis techniques (e.g., multilevel analyses, willingness to pay estimates). The course is structured as follows: Instructors will provide an overview on factorial survey experiments and explain practical tasks. Participants work on the tasks in individual “hands on” exercises. For the practical exercises, participants may choose a research question related to their own research (e.g., PhD project).

For most practical analyses, the statistical software package Stata will be used (prior knowledge required!). For setting up experimental designs and programming of questionnaires we use the software packages SAS and QuestBack (no prior knowledge required). The method is NOT connected to (confirmatory or explorative) factor analysis. Moreover, the course does not cover anchoring and video vignettes.

Course leader

Prof. Dr. Katrin Auspurg holds a full professorship in Sociology at the LMU Munich. Prof. Dr. Carsten Sauer holds a full professorship in Sociology at Bielefeld University. Sabine Düval is a research assistant at the LMU Munich, all Germany.

Target group

Participants will find the course useful if they:
- want to learn about survey-experimental designs to study attitudes or decisions;
- have initial ideas for their own research questions that could be realized by means of a factorial survey;
- plan to conduct a factorial survey in their projects;
- want to deepen their knowledge of experimental designs and quantitative statistical methods;
- want to learn how to analyze data from experimental designs and factorial surveys and evaluate the quality of such data.

Prerequisites:
Participants should
- be familiar with the statistical software package Stata before the course starts (i.e., command structure, do-files, ados);
- have basic knowledge of questionnaire design and experimental methods;
- have methodical knowledge of data management and quantitative data analyses (e.g. linear regression techniques, coding of variables, merging of data sets).

Course aim

By the end of the course participants will:
- have learned and discussed the features, typical applications, advantages, and shortcomings of factorial survey methods;
- have acquired practical insights into all single steps that are needed to set up factorial survey designs, to implement them into (computer assisted) questionnaires, to analyze resulting data, and report on results;
- be familiar with practical methods to evaluate data quality gained by factorial survey methods;
- have gained some insights into related experimental survey methods such as conjoint analyses and choice experiments;
- be able to apply factorial survey methods on their own.

Credits info

4 EC
- Certificate of attendance issued upon completion.
Optional bookings:
- 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 lectur-er(s) up to 4 weeks after the end of the summer school (EUR 50).

Fee info

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

Scholarships are available from the German Academic Exchange Service (DAAD) and the European Survey Research Association (ESRA)