dshare is an R package from the Centre d'Estudis d'Opinió to
estimate vote shares at the district level.
The package provides one function, dshare, which estimates a
multivariate (i.e., with several outcomes) Bayesian linear regression
through Stan. The left-hand side of the model
is a (factor) variable with the party choice for a respondent. The
right-hand side is a (factor) variable with the district of the
respondent. The coefficients of the regression are constrained to add
up to 1. The user can specify priors for the vote share in each
district.
The package can be used to estimate district-level vote shares when the number of observations in each district is small and the analyst has access to sensible priors (like previous electoral results). In essence, the model will calculate a weighted average between the priors and the observed vote shares in the data -- ensuring that the resulting shares are valid proportions.
Consider, for instance, the following cross tabulation of reported vote choice by district:
R> xtabs(~ intention + provincia, data=bop)
provincia
intention Barcelona Girona Lleida Tarragona
PPC 31 1 0 11
ERC 289 47 16 70
PSC 216 12 9 24
Cs 18 2 1 4
CUP 76 18 3 9
Junts.per.Catalunya 89 22 18 24
Catalunya.en.Comu.Podem 95 4 0 7
Vox 32 6 1 6
Altres.partits 21 6 1 4The sample size for most of the districts is too small to make reasonable inferences about vote choice using the data in the survey alone.
However, suppose that the analyst has some additional information about the support for each party in each district. This additional information can be expressed in the form of the following priors:
R> P
provincia
party Barcelona Girona Lleida Tarragona
PPC 0.0556 0.0285 0.0500 0.0591
ERC 0.2313 0.2577 0.3098 0.2773
PSC 0.2719 0.1719 0.1678 0.2176
Cs 0.0435 0.0242 0.0236 0.0373
CUP 0.0682 0.1018 0.0822 0.0734
Junts.per.Catalunya 0.1411 0.2682 0.2271 0.1525
Catalunya.en.Comu.Podem 0.0816 0.0444 0.0349 0.0517
Vox 0.0779 0.0640 0.0567 0.0937
Altres.partits 0.0291 0.0393 0.0477 0.0373The dshare estimates a model that combines the two pieces of
information. In this case, it estimates a Bayesian linear regression
between the declared intention of each respondent and their
provincia with priors centered around the analyst expectations with
a standard deviation (for each party in each district) of 0.025
points. The weights argument consumes the survey case weights. All
other arguments are passed directly to Stan and can be
used to control the sampling.
fit <- dshare(intention ~ provincia,
weights=weight,
data=bop,
priors=P,
sd=.025,
chains=3)The result from the model is
R> pestimates <- rstan::extract(fit) # Extracts samples
R> pestimates <- apply(pestimates$beta, c(2, 3), mean) # Averages over samples
R> dimnames(pestimates) <- dimnames(t(cfactors)) # Assigns dim names
R> t(pestimates)
provincia
party Barcelona Girona Lleida Tarragona
PPC 0.0523 0.0175 0.0358 0.0889
ERC 0.2304 0.2653 0.3020 0.2851
PSC 0.2828 0.1633 0.1734 0.2057
Cs 0.0383 0.0216 0.0266 0.0465
CUP 0.0705 0.1097 0.0753 0.0602
Junts.per.Catalunya 0.1319 0.2578 0.2684 0.1638
Catalunya.en.Comu.Podem 0.0889 0.0358 0.0256 0.0393
Vox 0.0774 0.0794 0.0550 0.0790
Altres.partits 0.0276 0.0496 0.0378 0.0315The package is not available on CRAN and must be installed from the GitHub repository directly.
install.packages("remotes")
remotes::install_github("ceopinio/dshare", subdir="dshare")