The course is based on a total survey error perspective and discusses the major sources of survey error. Participants will be presented with tools for detection and adjustment of such errors. Analysis methods are introduced using R statistical software. Knowledge of R is beneficial but not required if you have worked with SPSS, Stata, SAS or other statistical software already. Topics include coverage errors, complex sampling, nonresponse adjustment, measurement error, and analysis of incomplete data. Special attention will be given to the analysis of complex surveys that include weighting, stratification and design effects.
Changes in technology and society strongly influence modern survey research. This course covers the essentials of modern survey analysis and estimation and is organized by the Department of Methodology and Statistics (UU). Lectures, practical applications, and computer classes are alternated. The course is intended for advanced students and professionals in such fields as social and behavioral research, marketing, business, health sciences, and official statistics. The course is for researchers who intend to design and analyze their own survey, but also for researchers who analyze secondary data sets, such as the European Social Survey (ESS) or the International Social Survey Program (ISSP).
Central to the course is survey quality and the reduction of Total Survey Error (coverage, sampling, nonresponse, adjustment, measurement error, and processing error). Participants will be presented with tools for detection and adjustment of such errors. Analysis methods are introduced using R. Lectures and computer classes cover basic ideas from the TSE-perspective, sampling and non-sampling error: an introduction in R, survey estimation and inference, complex sampling, nonresponse adjustment, analysis of incomplete data, and measurement errors. Special attention will be given to the analysis of complex surveys - including weighting, stratification, and design effects - and to measurement in surveys.
This course assumes knowledge of survey methodology and statistics. Participants should be acquainted with Analysis of Variance, Multiple Regression Analysis, standard errors, and have some hands-on experience with statistical software such as SPSS, Stata, SAS. No prior knowledge of R is assumed.
A good preparation is our Summer School course ‘Survey Research: Design, Implementation and Data Processing’ (S15).
Participants need a laptop computer with R or SPSS installed for the computer practicals.
Lecturers
Bella Struminskaya (UU), Angelo Moretti (UU), Daniel Oberski (UU), Philip Brenner (UU)
Target audience
The course is intended for advanced students and professionals in such fields as social and behavioral research, marketing, business, health sciences, and official statistics. The course aims at researchers who intend to design and analyze their own survey, but also at researchers who analyze secondary data such as the European Social Survey (ESS) or the International Social Survey Program (ISSP).
This course assumes general knowledge of survey methodology and statistics. Participants should be acquainted with the basics of Analysis of Variance, Multiple Regression Analysis, standard errors, and have some hands-on experience with a statistical package (e.g., SPSS, Stata, SAS). No prior knowledge of R is assumed.
A maximum of 40 participants will be allowed to this course. Please note that the selection for this course will be done on a first-come-first-served basis.
Aim of the course
This course aims to provide participants with state of the art knowledge and application oriented skills for survey analysis and estimation. After the course, participants are ready to apply the learned towards their own data or archived data sets, and are able to take advanced training in complex survey statistics and adjustment..
For an overview of all our summer school courses offered by the Department of Methodology and Statistics please click here.
Study load
The course consists of formal lectures, less formal presentations or case studies, and practical exercises (with feedback) that apply the tools presented in the lectures. A typical course day starts at 9.00 and ends at 16.30 with breaks for coffee, lunch and tea. In general, the morning session consists of lectures and presentations, and the afternoon session is a computer lab where the topics of the morning are applied on example data. At the last day (Friday) after the morning program, there is the opportunity for individual consultation. Students who want to use this opportunity are expected to prepare for this in advance.
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 obtain a certificate upon completion of this course.
Costs
The 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.
There are no scholarships available for this course.
Additional information
We also offer tailormade M&S courses and in-house M&S training. If you want to look the possibilities, please contact us at ms.summerschool@uu.nl
Due to high demand on student housing we are currently fully booked.
If you wanted to book housing with us you can contact info@utrechtsummerschool.nl and be added to a waiting list. However, we cannot guarantee a room will be available and therefore we strongly advise to arrange accommodation yourself. Some suggestions can be found here: https://utrechtsummerschool.nl/housing/hotel-accommodation
Contact details
Team M&S Summer School | E: MS.summerschool@uu.nl