GESIS - DBK - ZA6803

ZA6803: Rolling Cross-Section Campaign Survey with Post-election Panel Wave (GLES 2017)

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ZA6803 Downloads and Data Access.


Data access



  • (Dataset) 2 KBytes
  • ZA6803_v4-0-1.dta (Dataset Stata) 8 MBytes
  • ZA6803_v4-0-1.sav (Dataset SPSS) 10 MBytes
  • ZA6803_v4-0-1_en.dta (Dataset Stata) 8 MBytes
  • ZA6803_v4-0-1_en.sav (Dataset SPSS) 10 MBytes
  • ZA6803_v4-0-1_open-ended.csv (Dataset) 773 KBytes



  • ZA6803_fb.pdf (Questionnaire) 1005 KBytes
  • ZA6803_q.pdf (Questionnaire) 993 KBytes

Other Documents


  • (Codeplan) 705 KBytes
  • ZA6803_sb.pdf (Study Description) 786 KBytes
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Bibliographic Citation

Citation Citation Roßteutscher, Sigrid; Schmitt-Beck, Rüdiger; Schoen, Harald; Weßels, Bernhard; Wolf, Christof; Staudt, Alexander (2019): Rolling Cross-Section Campaign Survey with Post-election Panel Wave (GLES 2017). GESIS Data Archive, Cologne. ZA6803 Data file Version 4.0.1,
Study No.ZA6803
TitleRolling Cross-Section Campaign Survey with Post-election Panel Wave (GLES 2017)
Current Version4.0.1, 2019-2-4,
Date of Collection24.07.2017 - 12.11.2017
Principal Investigator/ Authoring Entity, Institution
  • Roßteutscher, Sigrid - Universität Frankfurt
  • Schmitt-Beck, Rüdiger - Universität Mannheim
  • Schoen, Harald - Universität Mannheim
  • Weßels, Bernhard - Wissenschaftszentrum Berlin für Sozialforschung
  • Wolf, Christof - GESIS - Leibniz-Institut für Sozialwissenschaften
  • Staudt, Alexander - Universität Mannheim


Geographic Coverage
  • Germany (DE)
UniverseThe population comprises all German-speaking persons living in a private household with at least one landline or mobile phone in the Federal Republic of Germany, who are eligible to vote in the federal election of 2017.
Analysis Unit Analysis Unit
  • Individual
Sampling Procedure Sampling Procedure
  • Probability: Stratified: Proportional
Multistage random sampling with a dual selection frame based on the ADM-design (Gabler-Haeder-model for telephone samples). The pre-election wave is a Rolling Cross-Section (RCS) survey aiming to realize 120 interviews per day. These daily interviews were conducted in such a way that not only the entire sample, but also the interviews collected on each day constitute random samples from the population. Furthermore, the sample is regionally stratified. For landline users the selection of the target person in each household was selected via the last-birthday-method; for mobile phone users the person who answered the call was interviewed.
Mode of Collection Mode of Collection
  • Telephone interview: Computer-assisted (CATI)
Computer assisted telephone interview (CATI) with an average interview length of 31 minutes in the pre-election wave and 23 minutes in the post-election wave.
Time Method Time Method
  • Cross-section
Kind of Data Kind of Data
  • Numeric
  • Text
Data CollectorIPSOS
Date of Collection
  • 24.07.2017 - 12.11.2017

Errata & Versions

VersionDate, Name, DOI
4.0.1 (current version)2019-2-4 Release4-0-1
4.0.02018-9-10 Release4-0-0
3.0.12018-6-25 Release3-0-1
3.0.02018-5-30 Release3-0-0
2.0.02018-3-12 Release2-0-0
1.0.02017-12-13 first archive edition
Errata in current version
Version changes
Changes between version 4.0.1 and it's previous version
DateSubjectDescriptionCorrection Description
2019-2-5Variables „elecdist“, „elecdist_1“ - „elecdist_5“ and „elecdist_flag“ have been renamed to „elecdist17“, „elecdist17_1“ – „elecdist17_5“ and „elecdist17_flag“.2019-2-5
2019-2-5English versions of the dataset and the questionnaire have been added.2019-2-5
Changes between version 4.0.0 and it's previous version
DateSubjectDescriptionCorrection Description
2018-9-10Technic variables "generiert" and "pre_termin" have been added.2018-9-10
2018-9-10The marginal distributions of the weighting variables have been adjusted to the German micro census 2017.2018-9-10
2018-9-10The variable "bik10" has been removed due to data protection.2018-9-10
2018-9-10Editorial adjustments in variables "pos004a", "pos004b" and "elecdist"2018-9-10
Changes between version 3.0.1 and it's previous version
DateSubjectDescriptionCorrection Description
2018-6-25Missing value labels were added for variables pre073, pre074, pos013a, pos013b, and pos056a.2018-6-25
2018-6-25A typo in the labels of variables pre018a-pre018g has been fixed.2018-6-25
Changes between version 3.0.0 and it's previous version
DateSubjectDescriptionCorrection Description
2018-6-1The constituency coding has been added to the data set (elecdist, elecdist1-elecdist4, elecdist_flag).2018-6-1
2018-6-1The most important problem (MIP) and second MIP coding has been added for the pre- and post-election survey (pre013c1-pre013c5, pre015c1-pre015c5, pos015c1-pos015c5, pos017c1-pos017c5).2018-6-1
2018-6-1Post-stratification weights have been recalculated based on the marginal distributions from the German micro census 2016.2018-6-1
2018-6-1False variable labels in pre005 and pre007 have been fixed (the labels referred to first vote instead of second vote).2018-6-1
2018-6-1The tagnr variable has been converted from a string variable to a numeric variable.2018-6-1
Changes between version 2.0.0 and it's previous version
DateSubjectDescriptionCorrection Description
2018-3-12A panel weight has been added to the dataset.2018-3-12
2018-3-12Due to data protection provisions, answers to the questions about the most important and second most important political problem have been removed temporarily from the data set.2018-3-12
2018-3-12A coding error in the variable ostwest has been corrected.2018-3-12

Further Remarks

Number of Units: 7650
Number of Variables: 670
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.