Lecturers: Dr. Bella Struminskaya, Dr. Peter Lugtig
Date: 6-10 August 2018
Time: 09:00-13:00, 14:00-16:00
Short Course Description:
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, interviewer effects, questionnaire design, cognitive pretesting, assessing measurement errors and data editing. The course is taught from a Total Survey Error perspective weighing up 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 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 for the survey mode is discussed, and how different ways to sample respondents follow from that choice.
On the second day the issue of survey nonresponse is treated. 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 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.
- 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 3 2018.
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.
Course and Learning Objectives:
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.
- The course prepares the participants for more specialized courses at the GESIS Summer School.
Organizational structure of the course:
The course days contain four hours of classroom instruction and two hours of tutored individual and group exercises, during which the instructors are available for support. The lectures will include a mix of frontal teaching, short exercises and question-based discussions. The exercises will take place in the GESIS open study areas in the afternoon and are usually based on group work. There is no obligatory exercise planned for the last afternoon (August 10).
Software and hardware requirements:
None. This course does not include the use of statistical software.