BTLLasso (version 0.1-2)

GLES: German Longitudinal Election Study (GLES)

Description

Data from the German Longitudinal Election Study (GLES), see Rattinger et al. (2014). The GLES is a long-term study of the German electoral process. It collects pre- and post-election data for several federal elections, the data used here originate from the pre-election study for 2013.

Usage

data("GLES")

Format

A data frame with 1155 observations on the following 18 variables.

SPD vs FDP

Ordinal paired comparison between SPD and FDP

SPD vs Left Party

Ordinal paired comparison between SPD and Left Party

SPD vs Greens

Ordinal paired comparison between SPD and Greens

SPD vs CDU_CSU

Ordinal paired comparison between SPD and CDU/CSU

FDP vs Left Party

Ordinal paired comparison between FDP and Left Party

FDP vs Greens

Ordinal paired comparison between FDP and Greens

FDP vs CDU_CSU

Ordinal paired comparison between FDP and CDU/CSU

Left Party vs Greens

Ordinal paired comparison between Left Party and Greens

Left Party vs CDU_CSU

Ordinal paired comparison between Left Party and CDU/CSU

Greens vs CDU_CSU

Ordinal paired comparison between Greens and CDU/CSU

Age

Age in years

Gender

0: male, 1: female

EastWest

0: West Germany, 1:East Germany

PersEcon

Personal economic situation, 1: good or very good, 0: else

Abitur

School leaving certificate, 1: Abitur/A levels, 0: else

Unemployment

1: currently unemployed, 0: else

Church

Frequency of attendence in a church/synagogue/mosque/..., 1: at least once a month, 0: else

Migration

Have you been a German citizen since birth? 1: yes, 0: no

Source

http://www.gesis.org/en/elections-home/gles/data-and-documents/

Details

Variables 1 to 10 represent the response, variables 11 to 18 represent the subject-specific covariates. The response variables are ordinal, with values from 1 to 5. Low values represent string preference of the first-names party, high values represent strong preference of the last-named party.

References

Rattinger, H., S. Rossteutscher, R. Schmitt-Beck, B. Wessels, and C. Wolf (2014): Pre-election cross section (GLES 2013). GESIS Data Archive, Cologne ZA5700 Data file Version 2.0.0.

Schauberger, Gunther and Tutz, Gerhard (2015): Modelling Heterogeneity in Paired Comparison Data - an L1 Penalty Approach with an Application to Party Preference Data, Department of Statistics, LMU Munich, Technical Report 183

Examples

data(GLES)