GESIS - DBK - ZA6820
 

ZA6820: Long-term-Online-Tracking of State Election North Rhine-Westphalia 2017 (GLES)

Downloads and Data Access


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ZA6820 Downloads and Data Access

List of Files

List of Files
 

Datasets

  • ZA6820_missing.do (Dataset) 2 KBytes
  • ZA6820_v1-0-0.dta (Dataset Stata) 1 MByte
  • ZA6820_v1-0-0.sav (Dataset SPSS) 1 MByte
  • ZA6820_v1-0-0_open-ended.csv (Dataset) 46 KBytes

Questionnaires

  • ZA6820_fb.pdf (Questionnaire) 606 KBytes

Other Documents

  • ZA6800ff_GLES2017_Doku_insgesamt.zip (Codeplan) 234 KBytes
  • ZA6820_sb.pdf (Study Description) 447 KBytes
Availability Availability A - Data and documents are released for academic research and teaching.
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Bibliographic Citation

Citation Citation GLES (2017): Long-term-Online-Tracking of State Election North Rhine-Westphalia 2017 (GLES). GESIS Data Archive, Cologne. ZA6820 Data file Version 1.0.0, https://doi.org/10.4232/1.12852
Study No.ZA6820
TitleLong-term-Online-Tracking of State Election North Rhine-Westphalia 2017 (GLES)
Current Version1.0.0, 2017-8-10, https://doi.org/10.4232/1.12852
Date of Collection28.04.2017 - 13.05.2017
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
Contributor, Institution, Role
  • Roßteutscher, Sigrid - Universität Frankfurt - ProjectLeader
  • Bieber, Ina - Universität Frankfurt - ProjectManager
  • Henckel, Simon - Universität Frankfurt - ProjectMember
  • Scherer, Philipp - Universität Frankfurt - ProjectMember
  • Blinzler, Katharina - GESIS - Leibniz-Institut für Sozialwissenschaften - DataCurator

Methodology

Geographic Coverage
  • North Rhine-Westphalia (DE-NW)
UniverseThe population comprises all German citizens who were eligible to vote at the time the survey was conducted. Due to the fact that this is an online survey, not everybody who was eligible to vote had a probability to get selected for this Online Tracking. Therefore, the population comprises all persons with German citizenship resident in the Federal Republic of Germany who are part of the forsa omninet, who have a minimum age of 18 years, who live in North Rhine Westphalia and use the Internet at least once a week for private purposes. At the time the study was conducted, this group comprised approximately 2400 active Panel members. Active Panel members were recruited exclusively by phone, filled out a basic questionaire and attended at least one survey within the last twelve months.
Analysis Unit Analysis Unit
  • Individual
Sampling Procedure Sampling Procedure
  • Non-probability: Quota
Mode of Collection Mode of Collection
  • Self-administered questionnaire: Web-based (CAWI)
Time Method Time Method
  • Cross-section
Kind of Data Kind of Data
  • Numeric
  • Text
Data CollectorForsa.main Marktinformationssysteme GmbH, Frankfurt am Main
Date of Collection
  • 28.04.2017 - 13.05.2017

Errata & Versions

VersionDate, Name, DOI
1.0.0 (current version)2017-8-10 first archive edition https://doi.org/10.4232/1.12852
Errata in current version
none
Version changes

Further Remarks

Links
Number of Units: 521
Number of Variables: 701
Analysis System(s): SPSS, Stata

Publications

Relevant full texts
from SSOAR (automatically assigned)

Groups

Research Data Centre
Groups
  •  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.
  • State Elections in North Rhine-Westphalia