UKHouseOfCommons | R Documentation |

## 1992 United Kingdom electoral returns

### Description

Electoral returns, selected constituencies, 1992 general
election for the British House of Commons

### Usage

data(UKHouseOfCommons)

### Format

A data frame with 521 observations on the following 12 variables.

`constituency`

a character vector, name of the House of Commons constituency

`county`

a character vector, county of the House of Commons constituency

`y1`

a numeric vector, log-odds of Conservative to LibDem vote share

`y2`

a numeric vector, log-odds of Labor to LibDem vote share

`y1lag`

a numeric vector, `y1`

from previous election

`y2lag`

a numeric vector, `y2`

from previous election

`coninc`

a numeric vector, 1 if the incumbent is a
Conservative, 0 otherwise

`labinc`

a numeric vector, 1 if the incumbent is from
the Labor Party, 0 otherwise

`libinc`

a numeric vector, 1 if the incumbent is from
the LibDems, 0 otherwise

`v1`

a numeric vector, Conservative vote share
(proportion of 3 party vote)

`v2`

a numeric vector, Labor vote share (proportion of 3 party vote)

`v3`

a numeric vector, LibDem vote share (proportion of 3 party vote)

### Details

These data span only 521 of the 621 seats in the House of
Commons at the time of 1992 election. Seats missing either a Conservative,
Labor, or a LibDem candidate appear to have been dropped.

The original Katz and King data set does not have case labels. I
used matches to an additional data source to recover a set of constituency labels for
these data; labels could not recovered for two of the constituencies.

### Source

Jonathan Katz; Gary King. 1999. "Replication data for: A Statistical Model of Multiparty Electoral Data", http://hdl.handle.net/1902.1/QIGTWZYTLZ

### References

Katz, Jonathan and Gary King. 1999. “A Statistical Model for
Multiparty Electoral Data”. *American Political Science
Review*. 93(1): 15-32.

Jackman, Simon. 2009. *Bayesian Analysis for the Social
Sciences*. Wiley: Chichester. Example 6.9.

### Examples

data(UKHouseOfCommons)
tmp <- UKHouseOfCommons[,c("v1","v2","v3")]
summary(apply(tmp,1,sum))
col <- rep("black",dim(tmp)[1])
col[UKHouseOfCommons$coninc==1] <- "blue"
col[UKHouseOfCommons$labinc==1] <- "red"
col[UKHouseOfCommons$libinc==1] <- "orange"
library(vcd)
vcd::ternaryplot(tmp,
dimnames=c("Cons","Lab","Lib-Dem"),
labels="outside",
col=col,
pch=1,
main="1992 UK House of Commons Election",
cex=.75)