NOTE: this course is fully booked! New applicants will be placed on a waiting list.
This 4-day course in ‘ advanced survey design’ takes student beyond the introductory courses offered in BA and MA programmes, and will discuss the state of the art in both the design of surveys, and the analysis of survey data. We explicitly discuss new ways to analyse text data and sensor data generated by modern surveys. Course participants must be proficient in working with a package for statistical software (SATA, SAS, SPSS or R).
This 4-day course in survey design takes student beyond the introductory courses offered in BA and MA programmes, and discusses the state-of-the-art of one of the most important data collection techniques: surveys. The course focuses on the methodology of how to do surveys, and the use statistical techniques to analyse and correct for some specific survey errors. It combines short 1-hour lectures with exercises on most of the topics discussed.
Course participants must be proficient in working with a package for statistical software (SATA, SAS, SPSS or R). Course materials are prepared for working with R, while most of the exercises will also work with SPSS.
The course is interesting for social scientists or statisticians at the PhD level or beyond, working on academic research projects. Two courses are offered in the Utrecht Summer school that slightly overlap with this course: S15 (Survey Research: Design, Implementation and Data Processing) and S16 (Survey Research: Statistical Analysis and Estimation). The current course is however more advanced and more focused on survey research within the academic (university) setting.
We expect students to have some knowledge of survey research (for example by using survey data extensively) and have knowledge of statistics at the MsC level for social scientists (the general linear model).
Note: Participants need to bring a laptop computer to the course, with SPSS or alternatively with R ((https://www.r-project.org/) installed.
Day 1: Total Survey Error Paradigm. Choice of survey mode. The principles of probability sampling designs given different survey modes (simple random, cluster, stratified and multistage sampling).
Day 2: Questionnaire design, with specific attention to mixed-mode and mobile-device surveys.
Day 3: Cognitive pre-testing survey questions, the analysis of text data (using manual coding and machine learning). Nonresponse and weighting (both design and nonresponse weights).
Day 4: Paradata (what are they and how to use them?). Surveys and big data. Working with geo-location data to enrich survey data.
Tuition fee for PhD students from the Faculty of Social and Behavioural Sciences from Utrecht University will be funded by the Graduate School of Social and Behavioural Sciences.
PhD candidates from IOPS will be covered by IOPS.