gles: German Longitudinal Election Study

In MNLpred: Simulated Predicted Probabilities for Multinomial Logit Models

Description

A sample of 1,000 respondents in the Rolling Cross Sectional study in the German Longitudinal Election Study in 2017.

Usage

data(gles)

Format

An data frame with 1,000 observations and 6 variables:

vote

Voting decision for party

egoposition_immigration

Ego-position toward immigration (0 = very open to 10 = very restrictive )

ostwest

Dummy for respondents from Eastern Germany (= 1)

political_interest

Measurement for political interst (0 = low, 4 = high)

income

Self-reported income satisfaction (0 = low, 4 = high)

gender

Self-reported gender (binary coding with 1 = female)

Source

GESIS Datenarchiv

References

Roßteutscher, Sigrid et al. 2019. “Rolling Cross-Section-Wahlkampfstudie mit Nachwahl-Panelwelle (GLES 2017).” ZA6803 Datenfile Version 4.0.1. (GESIS Datenarchiv).

Examples

data(gles)
table(gles$vote)

MNLpred documentation built on July 16, 2021, 9:06 a.m.