GESIS - DBK - ZA6832

ZA6832: Longterm-Online-Tracking, Cumulation 2009-2017 (GLES)

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ZA6832 Downloads and Data Access

List of Files

List of Files


  • (Dataset) 2 KBytes
  • ZA6832_missing.sps (Dataset) 1 KByte
  • ZA6832_v1-1-0.dta (Dataset Stata) 77 MBytes
  • ZA6832_v1-1-0.sav (Dataset SPSS) 71 MBytes
  • ZA6832_v1-1-0_open-ended.csv (Dataset) 3 MBytes


  • (Questionnaire) 14 MBytes

Other Documents

  • (Codeplan) 2 MBytes
  • (Codeplan) 138 KBytes
  • ZA6832_Korrespondenzliste.pdf (Other Document) 6 MBytes
  • ZA6832_sb.pdf (Study Description) 2 MBytes
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Bibliographic Citation

Citation Citation GLES (2019): Longterm-Online-Tracking, Cumulation 2009-2017 (GLES). GESIS Data Archive, Cologne. ZA6832 Data file Version 1.1.0,
Study No.ZA6832
TitleLongterm-Online-Tracking, Cumulation 2009-2017 (GLES)
Current Version1.1.0, 2019-11-26,
Date of Collection18.09.2009 - 15.12.2017
Principal Investigator/ Authoring Entity, Institution
  • Rattinger, Hans - Universität Mannheim
  • Roßteutscher, Sigrid - Goethe-Universität Frankfurt am Main
  • Schmitt-Beck, Rüdiger - Universität Mannheim
  • Schoen, Harald - Universität Mannheim
  • Weßels, Bernhard - Wissenschaftszentrum Berlin für Sozialforschung
  • Wolf, Christof - GESIS – Leibniz-Institut für Sozialwissenschaften
Contributor, Institution, Role
  • Roßteutscher, Sigrid - Goethe-Universität Frankfurt am Main - ProjectLeader
  • Stövsand, Lars-Christopher - Goethe-Universität Frankfurt am Main - ProjectManager
  • Bühler, Pascal - Goethe-Universität Frankfurt am Main - ProjectMember
  • Dietz, Melanie - Goethe-Universität Frankfurt am Main - ProjectMember
  • Ehmes, Sven - Goethe-Universität Frankfurt am Main - ProjectMember
  • Scherer, Philipp - Goethe-Universität Frankfurt am Main - ProjectMember
  • Jungmann, Nils - GESIS – Leibniz-Institut für Sozialwissenschaften - DataCurator


Geographic Coverage
  • Germany (DE)
UniverseThe population comprises all German citizens who were eligible to vote when the survey was conducted. Due to the fact that this was an online survey not everybody who was eligible to vote had a chance to get selected for this Online Tracking. Therefore the population comprises all persons with German citizenship resident in the Federal Republic of Germany and being part of the respective access panel (until T16: Respondi AG, T17-T32: LINK, T33-T38: forsa omninet), who had a minimum age of 18 years. Active Panel members had been recruited by phone, had filled out a basic questionnaire and had participated in at least one survey within the last twelve months.
Analysis Unit Analysis Unit
  • Individual
Sampling Procedure Sampling Procedure
  • Non-probability: Quota
Sampling was based on a primarily defined ratio schedule (sex, age, education). Care is taken to ensure that panel members are only allowed to participate once a year in an Online Tracking of the GLES.
Mode of Collection Mode of Collection
  • Self-administered questionnaire: Web-based (CAWI)
Online Survey with standardized questionnaires
Time Method Time Method
  • Longitudinal: Trend/Repeated cross-section
Kind of Data Kind of Data
  • Numeric
  • Text
Data CollectorBamberger Centrum für Empirische Studien (BACES) LINK Institut für Markt- und Sozialforschung, Frankfurt am Main Forsa.main Marktinformationssysteme GmbH, Frankfurt am Main
Date of Collection
  • 18.09.2009 - 15.12.2017

Errata & Versions

VersionDate, Name, DOI
1.1.0 (current version)2019-11-26 Release 1.1.0
1.0.02019-11-14 first archive edition
Errata in current version
Version changes
Changes between version 1.1.0 and it's previous version
DateSubjectDescriptionCorrection Description
2019-11-26Editorial changes in variable labels2019-11-26
2019-11-26Recoding of system missings in k0570_1 - k0570_4 to -94 "not in sampling frame"2019-11-26
2019-11-26Publication of list of correspondence2019-11-26

Further Remarks

Number of Units: 34116
Number of Variables: 1943
Analysis System(s): SPSS, Stata


Relevant full texts
from SSOAR (automatically assigned)


Research Data Centre
  •  German Longitudinal Election Study (GLES)
    The German Longitudinal Election Study (GLES) is a DFG-funded project which made its debut just prior to the 2009 federal election. GLES is the largest and most ambitious election study held so far in Germany. Although the initial mandate is to examine and analyse the electorate for three consecutive elections, the aspired goal is to integrate the project within GESIS as an institutionalized election study after the federal election of 2017, and hence to make it a permanent study.