bes83 | R Documentation |
Subsample from British Election Study, consisting of 800 voters across 110 areas.
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.
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).
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.
## 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)
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