anominate {anominate}R Documentation

alpha-NOMINATE: Ideal Point Estimator

Description

anominate is the function that takes a rollcall object and fits the Bayesian (MCMC-based) alpha-NOMINATE model described in Carroll et al. (2013). The method estimates the structure of political actors' utility functions from roll call data with the inclusion of a separate parameter denoted as alpha. alpha values of 1 indicate normal (Gaussian) utility, while alpha values of 0 indicate quadratic utility.

Usage

anominate(rcObject, dims=1, nsamp=1000, thin=1, burnin=500, minvotes=20, 
	lop=0.025, polarity=1, random.starts=TRUE, verbose=FALSE, constrain=FALSE)

Arguments

rcObject

An object of class rollcall, from Simon Jackman's pscl package.

dims

integer, number of dimensions to estimate. Must be nonnegative and cannot exceed 10 dimensions.

nsamp

interger, total number of iterations for the sampler. nsamp divided by thin must be larger than burnin.

thin

integer, thinning interval for the MCMC samples.

burnin

integer, number of iterations to be discarded.

minvotes

integer, minimum number of votes required for a legislator to be included in the analysis.

lop

A proportion between 0 and 1, the cut-off used for excluding lopsided votes, expressed as the proportion of non-missing votes on the minority side. The default, lop=0.025, eliminates votes where the minority is smaller than 2.5 overwrites the lopsided attribute in the rollcall object inputted.

polarity

a vector specifying the legislator in the data set who is conservative on each dimension. For example, c(3,5) indicates legislator 3 is conservative on dimension 1, and legislator 5 is conservative on dimension 2. Alternatively, polarity can be specified as a string for legislator names found in legis.names (i.e., c("Bush", "Gore")) if every legislative name in the data set is unique. Finally, polarity can be specified as a list (i.e., list("cd",c(4,5))) where the first list item is a variable from the roll call object's legis.data, and the second list item is a conservative legislator on each dimension as specified by the first list item. list("cd",c(4,5)) thus specifies the legislators with congressional district numbers of 4 and 5.

random.starts

logical, indicating whether initial values for the legislator and bill parameters should be randomly drawn from a uniform distribution. If FALSE, the W-NOMINATE estimates are used as the initial values.

verbose

logical, indicates whether the progress of W-NOMINATE and alpha-NOMINATE (at each 100th iteration of the MCMC sampler) should be printed to the screen.

constrain

logical, indicates whether alpha should be constrained to equal 1 rather than estimated. This option should be used if more than one dimension is being estimated, which makes the method equivalent to a Bayesian implementation of Poole and Rosenthal's (1997) NOMINATE model.

Value

An object of class anominate, which in this documentation is also referred to as an alpha-NOMINATE object.

alpha

An object of class mcmc with the sampled values of the alpha parameter.

beta

An object of class mcmc with the sampled values of the beta parameter.

legislators

A object of class mcmc with the sampled values of the legislator ideal points, with each dimension stored in a separate list (e.g., the first dimension coordinates are stored in legislators[[1]], the second dimension coordinates in legislators[[2]], etc.).

yea.locations

A object of class mcmc with the sampled values of the Yea locations (midpoint - spread in W-NOMINATE) for each vote, with each dimension stored in a separate list (e.g., the first dimension coordinates are stored in yea.locations[[1]], the second dimension coordinates in yea.locations[[2]], etc.).

nay.locations

A object of class mcmc with the sampled values of the Nay locations (midpoint + spread in W-NOMINATE) for each vote, with each dimension stored in a separate list (e.g., the first dimension coordinates are stored in nay.locations[[1]], the second dimension coordinates in nay.locations[[2]], etc.).

wnom.result

An object of class nomObject with the W-NOMINATE (wnominate) results.

Author(s)

Royce Carroll rcarroll@rice.edu

Christopher Hare cdhare@ucdavis.edu

Jeffrey B. Lewis jblewis@ucla.edu

James Lo lo@uni-mannheim.de

Keith T. Poole ktpoole@uga.edu

Howard Rosenthal hl31@nyu.edu

References

Royce Carroll, Jeffrey B. Lewis, James Lo, Keith T. Poole and Howard Rosenthal. 2013. “The Structure of Utility in Spatial Models of Voting.”' American Journal of Political Science 57(4): 1008-1028.

Jeffrey B. Lewis. https://voteview.com/

Keith Poole and Howard Rosenthal. 1997. Congress: A Political-Economic History of Roll Call Voting. New York: Oxford University Press.

See Also

'summary.anominate','plot.anominate','densplot.anominate','traceplot.anominate','simulateData', 'sen111', 'sen111_anom', 'rollcall'.

Examples

  data(sen111)
   
  sen111_anom <- anominate(sen111, dims=1, polarity=2, 
   nsamp=200, thin=1, burnin=100, random.starts=FALSE, 
   verbose=FALSE, constrain=FALSE)
  
  # 'sen111_anom' can be retrieved quickly with: 
  data(sen111_anom)
  
  # Summary statistics:
  summary(sen111_anom)
  # Graphical summaries:
  plot(sen111_anom)
  densplot.anominate(sen111_anom)
  traceplot.anominate(sen111_anom)

[Package anominate version 0.7 Index]