This course in ‘advanced survey design’ takes students beyond the introductory courses and will discuss the state of the art in both the design and the analysis of survey data. We discuss new ways to analyse modern surveys, including non-probability survey designs, and surveys conducted via apps. Course participants must be proficient working with the statistical software package R at the level of at least knowing Tidy and multivariate regression in R.
This 5-day course in survey design takes students beyond the introductory courses offered in BA and MA programmes, and discusses current issues in one of the most important data collection methods: surveys. Specifically, it focuses on doing surveys in the Internet-era. It will discuss how to collect data in online surveys, using smartphones, and mixing surveys with Big data. It combines short 1-hour lectures with exercises on most of the topics discussed. Course participants must be fully proficient in working with a package for statistical software. Course materials are prepared for working with R.
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, as well as focused on current issues related to mobile surveys and Big Data.
We expect students to have quite extensive knowledge of survey research (for example by using survey data extensively or conducting survey research in their daily work) and have knowledge of statistics at the MSc level for social scientists (the general linear model). Note that you have to upload a brief motivation letter (up to 300 words) with your application, in which you 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.
IOPS students do not have to do this.
Note: Participants need to bring a laptop computer to the course with R (https://www.r-project.org/) installed and the ability to download packages (Internet access is provided).
Day 1: design and sampling
- Total Survey Error in the context of ‘designed Big data’
- Brief overview of probability sampling methods, and the survey package in R.
- Exercises on sampling with R
Day 2: Questionnaire design
- Mixed modes (incl. web)
- Pretesting questionnaires
- Mobile surveys
- Questionnaires in context of admin and big data
Day 3: Nonresponse, correcting for nonresponse and other representation errors.
- Design weights and constructing nonresponse weights
- Process data or Paradata
- The choice of whether to impute or weight for missing data
- Exercises in R
Day 4: Surveys and big data.
- The collection, analysis, and integration of different types of organic data, and more traditional survey data.
- Data collection through apps, sensors, and wearables.
We provide exercises on working with geo-locations, and other sensor data (e.g. pictures, accelerometers)
Day 5: The collection of data via apps (continued from day 4
- The collection and analysis of survey and sensor data collected via mobile apps
- Consultations about your own research project
Dr. Bella Struminskaya, Dr. Peter Lugtig
If you want to know the current state of the art in survey data and survey data analysis, this is a course for you. This course assumes minimally MSc level knowledge of methods and statistics. In the course R will be used extensively, and knowledge of R is presumed. The course is intended for PhD students, and others at the postgraduate level who wish to know more of survey data and its collection in the 21st century.
A maximum of 50 participants will be allowed in this course. IOPS students will get priority.
Aim of the course
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. After the course, participants are ready to apply the learned towards their own surveys, are able to critically assess existing surveys and survey documentation and analyse survey data themselves successfully.
For an overview of all our summer school courses offered by the Department of Methodology and Statistics please click here.
The course consists of 1-hour lectures mixed with 1-hour exercises using the computer, to apply the tools presented in the lectures. A typical course day starts at 9.30 and ends at 16.30 with breaks for coffee, lunch and tea (included in the course fee). Everyone actively participating on all five days of the course will qualify for ECs. (2 EC). Certificates of attendance will be handed out at the end of the course. There is no reading required before the start of the course. However, we will provide an overview of further reading with every formal lecture on a topic.
Please note that there are no graded activities included in this course. Therefore, we are not able to provide students with a transcript of grades. You will however obtain a certificate upon completion of this course.
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.
There are no scholarships available for this course.
Please upload a brief motivation letter (up to 300 words) with your application, in which you 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. IOPS students do not have to do this, you can upload a blank document.
For this course you are required to upload the following documents when applying:
Irma Reyersen | E: firstname.lastname@example.org