R2MLwiN (version 0.8-2)

bes83: Subsample from British Election Study, '83.

Description

Subsample from British Election Study, consisting of 800 voters across 110 areas.

Format

A data frame with 800 observations on the following 10 variables:

voter

Voter identifier.

area

Identifier for voters' constituencies.

defence

Score on a 21 point scale of attitudes towards nuclear weapons with low scores indicating disapproval of Britain possessing them. This variable is centred about its mean.

unemp

Score on a 21 point scale of attitudes towards unemployment with low scores indicating strong opposition and higher scores indicating a preference for greater unemployment if it results in lower inflation. This variable is centred about its mean.

taxes

Score on a 21 point scale of attitudes towards tax cuts with low scores indicating a preference for higher taxes to pay for more government spending. This variable is centred about its mean.

privat

Score on a 21 point scale of attitudes towards privatization of public services with low scores indicating opposition. This variable is centred about its mean.

votecons

If respondent voted Conservative; a factor with levels Other and Voted_Conservative.

cons

This variable is constant (= 1) for all voters.

denom

This variable is constant (= 1) for all voters.

Source

Browne, W. J. (2012) MCMC Estimation in MLwiN Version 2.26. University of Bristol: Centre for Multilevel Modelling. Heath, A., Yang, M., Goldstein, H. (1996). Multilevel analysis of the changing relationship between class and party in Britain 1964-1992. Quality and Quantity, 30:389-404. Rasbash, J., Charlton, C., Browne, W.J., Healy, M. and Cameron, B. (2009) MLwiN Version 2.1. Centre for Multilevel Modelling, University of Bristol. Rasbash, J., Steele, F., Browne, W.J. and Goldstein, H. (2012) A User's Guide to MLwiN Version 2.26. Centre for Multilevel Modelling, University of Bristol.

Details

The bes83 dataset is one of the sample datasets provided with the multilevel-modelling software package MLwiN (Rasbash et al., 2009). See Heath et al (1996), and also Rasbash et al (2012) and Browne (2012).

Examples

## Not run: 
# 
# data(bes83, package = "R2MLwiN")
# 
# (mymodel <- runMLwiN(logit(votecons, cons) ~ 1 + defence + unemp + taxes + privat + (1 | area),
#   D = "Binomial", estoptions = list(EstM = 1), data = bes83))
# 
# ## End(Not run)