Scientific Coordination
Sebastian E. Wenz
Tel: +49 221 47694-159
Tel: +49 221 47694-159
Administrative Coordination
Jacqueline Schüller
Tel: +49 0221 47694-160
Tel: +49 0221 47694-160
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Course 6: Designing, Implementing, and Analyzing Longitudinal Surveys
About
Location:
Cologne/Unter Sachsenhausen 6-8
Cologne/Unter Sachsenhausen 6-8
Course Duration
Mo-Fr: 10:00-17:00 CEST
General Topics:
Course Level:
Format:
Software used:
Duration:
Language:
Fees:
Students: 550 €
Academics: 825 €
Commercial: 1650 €
Additional links
Lecturer(s): Alexandru Cernat, Tarek Al Baghal
Course description
Longitudinal data are essential for understanding individual level change and are used in multiple social science fields such as sociology, psychology, economics, health and so on. Collecting such data brings with it specific challenges that are not present in cross-sectional surveys. The course will provide an overview of those aspects of survey design, implementation, and analysis that are unique to longitudinal surveys or that have distinct features in the longitudinal context. The course is unique in that it focuses on how to collect longitudinal data (4 days) and less on how to analyze data (1 day).
The full syllabus of the course including the day-to-day schedule will be published here in April.
Target group
You will find the course useful if:
- you are interested in the uses and importance of longitudinal surveys,
- you are involved in planning or conducting a longitudinal survey,
- you are interested aspects of longitudinal data collection, including data linkage,
- you are involved in the measurement of phenomena over time,
- you want to use appropriate methods to analyze longitudinal data.
Learning objectives
By the end of the course, you will:
- be familiar with the central design issues of longitudinal surveys,
- understand different strategies on how to collect longitudinal data,
- be able to design questions that meet research objectives for longitudinal surveys and minimize error,
- understand methods to link new sources of data to longitudinal surveys,
- be able to identify and implement features that should help to prevent panel attrition,
- be able to study the nature of non-response and attrition in a longitudinal survey,
- understand generally the methods used in weighting and imputation in a panel survey.
Organizational structure of the course
- Every day will include both lectures and practical applications of what is being covered in the lectures. Practical applications will occur near the middle of the lectures and at the end of the lectures.
- In these meetings, practical applications will be given for you to work through, with the opportunity to ask instructors questions one-on-one about the course or your own projects.
- The practical application will relate to topics in longitudinal survey design covered in the lectures, including the impact of question wording on measurement, the identification of attrition, the development of weights, and how these can impact analytic findings.
- After the individual work, the lecturer will go through the solutions with the entire class.
- Analysis done during practical applications will use Stata or R.
Prerequisites
- Basic knowledge of survey methodology from a cross-sectional perspective, in particular with respect to survey design, instrument development, and survey implementation.
- Basic knowledge of statistics and statistical modelling (i.e., regression) and of a statistical software (Stata or R).
Software and hardware requirements
You will need to bring a laptop computer to successfully participate in this course.
You may use R or Stata for exercises. GESIS will provide a Stata short term license for the duration of the course if needed. R users should install R (https://cran.r-project.org/) and RStudio (https://www.rstudio.com/) before the start of the course. R packages needed: tidyverse, haven, sample, lme4, plm, broom.
