R: W-NOMINATE Roll Call Scaling

wnominate {wnominate}

R Documentation

W-NOMINATE Roll Call Scaling

Description

wnominate is the function that takes a rollcall object and estimates Poole and Rosenthal W-NOMINATE scores with them.

Usage

wnominate(rcObject, ubeta=15, uweights=0.5, dims=2, minvotes=20,
        lop=0.025,trials=3, polarity, verbose=FALSE)

Arguments

`rcObject`	An object of class `rollcall`, from Simon Jackman's `pscl` package.
`ubeta`	integer, beta parameter for NOMINATE. It is strongly recommended that you do not change the default.
`uweights`	integer, weight parameter for NOMINATE. It is strongly recommended that you do not change the default.
`dims`	integer, number of dimensions to estimate. Must be nonnegative and cannot exceed 10 dimensions.
`minvotes`	minimum number of votes a legislator must vote in for them to be analyzed.
`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 RC object inputted.
`trials`	integer, number of bootstrap trials for standard errors. Any number set below 4 here will not return any standard errors. Setting this number to be large will slow execution of W-NOMINATE considerably.
`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` (ie. `c("Bush", "Gore")`) if every legislative name in the data set is unique. Finally, polarity can be specified as a list (ie. `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.
`verbose`	logical, indicates whether bills and legislators to be deleted should be printed while data is being checked before ideal points are estimated.

Value

An object of class nomObject, which in this documentation is also referred to as a W-NOMINATE object.

`legislators`	data frame, containing all data from the old `nom31.dat` file about legislators. For a typical W-NOMINATE object run with an ORD file read using `readKH`, it will contain the following: `state` State name of legislator. `icpsrState` ICPSR state code of legislator. `cd` Congressional District number. `icpsrLegis` ICPSR code of legislator. `party` Party of legislator. `partyCode` ICPSR party code of legislator. `correctYea` Predicted Yeas and Actual Yeas. `wrongYea` Predicted Yeas and Actual Nays. `wrongNay` Predicted Nays and Actual Yeas. `correctNay` Predicted Nays and Actual Nays. `GMP` Geometric Mean Probability. `CC` Correct Classification. `coord1D` First dimension W-NOMINATE score, with all subsequent dimensions numbered similarly. `se1D` Bootstrapped standard error of first dimension W-NOMINATE score, with all subsequent dimensions numbered similarly. This will be empty if trials is set below 4. `corr.1` Covariance between first and second dimension W-NOMINATE score, with all subsequent dimensions numbered similarly.
`rollcalls`	data frame, containing all data from the old `nom33.dat` file about bills. For a typical W-NOMINATE object run with an ORD file read using `readKH`, it will contain the following: `correctYea` Predicted Yeas and Actual Yeas. `wrongYea` Predicted Yeas and Actual Nays. `wrongNay` Predicted Nays and Actual Yeas. `correctNay` Predicted Nays and Actual Nays. `GMP` Geometric Mean Probability. `PRE` Proportional Reduction In Error. `spread1D` First dimension W-NOMINATE spread, with all subsequent dimensions numbered similarly. `midpoint1D` First dimension W-NOMINATE midpoint, with all subsequent dimensions numbered similarly.
`dimensions`	integer, number of dimensions estimated.
`eigenvalues`	A vector of roll call eigenvalues.
`beta`	The beta value used in the final iteration.
`weights`	A vector of weights used in each iteration.
`fits`	A vector of length 3*dimensions with the classic measures of fit. In order, it contains the correct classifications for each dimension, the APREs for each dimension, and the overall GMPs for each dimension.

Author(s)

Keith Poole ktpoole@uga.edu

Jeffrey Lewis jblewis@ucla.edu

James Lo lojames@usc.edu

Royce Carroll rcarroll@rice.edu

References

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

Jeffrey Lewis. https://voteview.com/

Keith Poole, Jeffrey Lewis, James Lo, and Royce Carroll. 2011. ‘Scaling Roll Call Votes with WNOMINATE in R.’ Journal of Statistical Software, 42(14), 1-21. https://www.jstatsoft.org/v42/i14/

Examples

    #This data file is the same as reading file using:
    #sen90 <- readKH("ftp://voteview.com/sen90kh.ord")
    #All ORD files can be found on www.voteview.com
    data(sen90)
    
    summary(sen90)
    #sen90wnom <- wnominate(sen90,polarity=c(2,5))
    #'sen90wnom' is the same nomObject as found in 
    data(sen90wnom)
    summary(sen90wnom)
    plot(sen90wnom)

[Package wnominate version 1.5 Index]