gnm (version 0.9-2)

voting: Data on Social Mobility and the Labour Vote

Description

Voting data from the 1987 British general election, cross-classified by the class of the head of household and the class of their father.

Usage

data(voting)

source

Clifford, P. and Heath, A. F. (1993) The Political Consequences of Social Mobility. J. Roy. Stat. Soc. A, 156(1), 51-61.

Examples

### Examples from Clifford and Heath paper
### (Results differ slightly - possible transcription error in
### published data?)
set.seed(1)
data(voting)
## reconstruct counts voting Labour/non-Labour
count <- with(voting, percentage/100 * total)
yvar <- cbind(count, voting$total - count)

## fit diagonal reference model with constant weights
classMobility <- gnm(yvar ~ -1 + Dref(origin, destination), 
                     family = binomial, data = voting)
prop.table(exp(coef(classMobility)[1:2]))

## create factors indicating movement in and out of salariat (class 1)
upward <- with(voting, origin != 1 & destination == 1)
downward <- with(voting, origin == 1 & destination != 1)

## fit separate weights for the "socially mobile" groups
socialMobility <- gnm(yvar ~ -1 + Dref(origin, destination,
                                       delta = ~ 1 + downward + upward),
                      family = binomial, data = voting)
coefs <- coef(socialMobility)
baseline <- coefs[pickCoef(socialMobility, "(Intercept)")]
upwardTRUE <- coefs[pickCoef(socialMobility, "upwardTRUE")]
downwardTRUE <- coefs[pickCoef(socialMobility, "downwardTRUE")]
prop.table(exp(baseline))
prop.table(exp(upwardTRUE + baseline))
prop.table(exp(downwardTRUE + baseline))

## fit separate weights for downwardly mobile groups only
downwardMobility <- gnm(yvar ~ -1 + Dref(origin, destination,
                                         delta = ~ 1 + downward),
                        family = binomial, data = voting)
downwardMobility
coefs <- coef(downwardMobility)
baseline <- coefs[pickCoef(downwardMobility, "(Intercept)")]
downwardTRUE <- coefs[pickCoef(downwardMobility, "downwardTRUE")]
prop.table(exp(baseline))
prop.table(exp(downwardTRUE + baseline))