GESIS - DBK - ZA5732
 

ZA5732: Long-term Online Tracking, T32 (GLES)

Downloads and Data Access


On this page you find the complete metadata and an overview of all available data sets and documents for the requested study. The download of all files is possible from our central search page under the following link:
ZA5732 Downloads and Data Access

List of Files

List of Files
 

Datasets

  • ZA5732_missing.do (Dataset) 2 KBytes
  • ZA5732_open-ended_v1-0-0.csv (Dataset) 65 KBytes
  • ZA5732_v1-0-0.dta (Dataset Stata) 1 MByte
  • ZA5732_v1-0-0.sav (Dataset SPSS) 1 MByte

Questionnaires

  • ZA5732_fb.pdf (Questionnaire) 596 KBytes

Other Documents

  • ZA5700ff_GLES2013_Doku_insgesamt.zip (Codeplan) 138 KBytes
  • ZA5732_sb.pdf (Study Description) 911 KBytes
Availability Availability A - Data and documents are released for academic research and teaching.
Download of Data and Documents Download of Data and Documents All downloads from this catalogue are free of charge. Data-sets available under access categories B and C must be ordered via the shopping cart with a few exceptions. Charges apply! Please respect our Terms of use.


Bibliographic Citation

Citation Citation GLES (2016): Long-term Online Tracking, T32 (GLES). GESIS Data Archive, Cologne. ZA5732 Data file Version 1.0.0, https://doi.org/10.4232/1.12625
Study No.ZA5732
TitleLong-term Online Tracking, T32 (GLES)
Current Version1.0.0, 2016-9-7, https://doi.org/10.4232/1.12625
Date of Collection03.06.2016 - 17.06.2016
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
  • Henckel, Simon - Universität Frankfurt - ProjectManager
  • Bieber, Ina - Universität Frankfurt - ProjectMember
  • Scherer, Philipp - Universität Frankfurt - ProjectMember
  • Kaukal, Malte - GESIS - Leibniz-Institut für Sozialwissenschaften - DataCurator

Content

Topics Topics
  • 2.2 Migration
  • 9.2 Mass media
  • 11.2 International politics and organisation
  • 11.5 Mass political behaviour, attitudes/opinion
  • 11.6 Government, political systems and organisation
  • 11.7 Elections
  • 17.5 Economic policy
  • 17.6 Economic systems and development

Methodology

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 probability 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 forsa omninet, who had a minimum age of 18 years, who lived in Germany and used at least once a week the Internet for private reasons. In this survey only members of the former LINK Internet Panel were included of the forsa omninet. This group comprised nearly 43000 active Panel members. Panel members were recruited exclusively by phone.
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
  • 03.06.2016 - 17.06.2016

Errata & Versions

VersionDate, Name, DOI
1.0.0 (current version)2016-9-7 first archive edition https://doi.org/10.4232/1.12625
Errata in current version
DateSubjectDescription
2016-11-4The coding in variable t320 "Frequency church attendance" is partly wrong. Value -97 "not applicable" is supposed to be -99 "no answer". The current -99 should be -98 "don´t know".
Version changes

Further Remarks

Links
Number of Units: 1023
Number of Variables: 527
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.