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

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Jacqueline Schüller
Tel: +49 0221 47694-160

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Course 1: Designing, Implementing, and Analyzing Longitudinal Surveys

About
Location:
Cologne / Unter Sachsenhausen 6-8
 
Course duration:
10:00-17:00 CEST
General Topics:
Survey Methodology, Data Analysis
Course Level:
Advanced
Format:
Summer School
Software used:
R and Stata
Duration:
5 days
Language:
English
Fees:
Students: 500 €
Academics: 750 €
Commercial: 1500 €
 
Keywords
Additional links
Lecturer(s): Tarek Al Baghal, Alexandru Cernat

About the lecturer - Tarek Al Baghal

About the lecturer - Alexandru Cernat

Course description

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 potential to add various data sources to longitudinal studies and its uses, such as administrative data, biomarkers, and social media/web-scraped data.
  • 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, there will be exercises throughout each day for practical applications of lectures and methods taught practical application of these methods and provide an opportunity for more interaction with the instructors.
     
    A detailed syllabus with course times and literature will soon be available for download here.


    Target group

    Participants will find the course useful if:
  • 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, including data linkage.
  • they are in the processes involved in measurement of phenomena over time.
  • they want to use appropriate methods to analyse longitudinal data.


    • Learning objectives

    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.
  • 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
  • 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.
  • Analysis done during practical applications will use Stata or R.


    • Prerequisites

  • 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
    Participants will need to bring a laptop computer to successfully participate in this course. Participants may use R or Stata for exercises. Stata users may receive a Stata short term license provided by GESIS for the duration of the course if needed. R users should have installed a recent version of R (R packages needed: tidyverse, haven, sample, lme4, plm, broom).