GESIS Training Courses

Wiss. Koordination

Sebastian E. Wenz
Tel: +49 221 47694-159

Administrative Koordination

Angelika Ruf
Tel: +49 221 47694-162

Course 7: Designing, Implementing, and Analyzing Longitudinal Surveys

Dr. Tarek Al Baghal, Dr. Alexandru Cernat

Datum: 17.08 - 21.08.2020 ics-Datei

Veranstaltungsort: Online via Zoom

Referenteninformationen - Dr. Tarek Al Baghal

Referenteninformationen - Dr. Alexandru Cernat


[This is a 30 hour class.]
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 will specifically cover:
  • A review of the advantages and limitations of longitudinal surveys and an outline of some of the uses to which longitudinal surveys are put.
  • Key aspects of longitudinal survey design such as the sampling design, interval between waves, and data collection modes.
  • Important aspects of designing a questionnaire and measurement for longitudinal studies, particularly for capturing micro-level change
  • The impact of non-response and attrition in a panel, and adjustments such as weighting and imputation given that missing data patterns differ between waves.
  • An introduction to important analysis considerations and methods when using a longitudinal survey design.
  • In addition, each morning time will be available in a computer lab for exercises for practical application of these methods and an opportunity for more interaction with the instructors.
A detailed syllabus for this course is available for download here.



  • they are interested in the uses and importance of longitudinal surveys ;
  • they are involved in planning or conducting a longitudinal survey;
  • they are interested aspects of longitudinal data collection;
  • they are in the processes involved in measurement of phenomena over time;
  • they want to use appropriate methods to analyze longitudinal data.


By the end of the course participants 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;
  • 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:
This is a five-day course with a total amount of 30 hours of virtual class time. Participants can expect a mix of interactive teaching and exercises. Exercises (in Stata and/or R) are designed to deepen their understanding of the course material.
  • In these meetings, practical applications will be given for the students to work through, with the opportunity to ask instructors questions one-on-one about the course or their 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. Practical sessions will use Stata or R.


  • participants should have 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:
We will use Stata and R for practical exercises. Participants who do not own a copy of Stata will be provided with access to a full Stata licence by GESIS for the duration of the course. Stata will be installed and activated prior to the course by GESIS staff through remote access on the participants' machines. Participants who (also) wish to use R should have a recent version of R ( and Rstudio installed ( Both programs are free and open source. For R the following packages should be installed: tidyverse, haven, sample, lme4, plm, broom.