dwnom | R Documentation |
This data set contains materials related to the Poole-Rosenthal DW-NOMINATE measure of senator
ideology. The software (and other materials) is available at https://voteview.com/,
which includes a simpler example of an application to the 80-110 U.S. Senate. The data set here is
derived from the data and estimates from that example, but are formatted to be run in hierIRT()
.
In particular, start values for estimation are identical to those provided by the example.
data(dwnom)
dwnom |
list, containing the following elements:
|
DW-NOMINATE is described in Keith T. Poole and Howard Rosenthal. 1997. Congress: A Political Economic History of Roll Call Voting. Oxford University Press. See also https://voteview.com/.
Variational model is described in Kosuke Imai, James Lo, and Jonathan Olmsted (2016). “Fast Estimation of Ideal Points with Massive Data.” American Political Science Review, Vol. 110, No. 4 (December), pp. 631-656.
'hierIRT'.
### Real data example of US Senate 80-110 (not run) ### Based on voteview.com example of DW-NOMINATE ### We estimate a hierarchical model without noise and a linear time covariate ### This model corresponds very closely to the DW-NOMINATE model ## Not run: data(dwnom) ## This takes about 10 minutes to run on 8 threads ## You may need to reduce threads depending on what your machine can support lout <- hierIRT(.data = dwnom$data.in, .starts = dwnom$cur, .priors = dwnom$priors, .control = {list( threads = 8, verbose = TRUE, thresh = 1e-4, maxit=200, checkfreq=1 )}) ## Bind ideal point estimates back to legislator data final <- cbind(dwnom$legis, idealpt.hier=lout$means$x_implied) ## These are estimates from DW-NOMINATE as given on the Voteview example ## From file "SL80110C21.DAT" nomres <- dwnom$nomres ## Merge the DW-NOMINATE estimates to model results by legislator ID ## Check correlation between hierIRT() and DW-NOMINATE scores res <- merge(final, nomres, by=c("senate","id"),all.x=TRUE,all.y=FALSE) cor(res$idealpt.hier, res$dwnom1d) ## End(Not run)
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