sen90wnom {wnominate}

90th U.S. Senate Ideal Points

Description

This dataframe contains the estimated ideal points of the 90th U.S Senate using wnominate. Although it can easily be obtained from calling the example in wnominate, it is included here to facilitate illustration of the examples for the plot and summary functions.

Usage

data(sen90wnom)

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 nom33.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.

• PRE Proportional Reduction In Error.

• 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 [e-mail]

Jeffrey Lewis [e-mail]

James Lo [e-mail]

Royce Carroll [e-mail]

Source

Keith Poole. 2005. 90th Senate Roll Call Vote Data. https://www.voteview.com/.

See Also

'wnominate'.

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)