oc {oc}R Documentation

Optimal Classification Roll Call Scaling

Description

oc is the function that takes a rollcall object and estimates nonmetric Optimal Classification scores with them.

Usage

oc(rcObject, dims=2, minvotes=20, lop=0.025, polarity, verbose=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.
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.
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 OCobject, with elements as follows:

legislators data frame, containing all data from the old perf25.dat file about legislators. For a typical ocObject 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.
    rank
    Rank ordering of legislator on the first dimension, from lowest to highest.
    correctYea
    Predicted Yeas and Actual Yeas.
    wrongYea
    Predicted Yeas and Actual Nays.
    wrongNay
    Predicted Nays and Actual Yeas.
    correctNay
    Predicted Nays and Actual Nays.
    volume
    Measure of the legislator's polytope size.
    coord1D
    First dimension OC score, with all subsequent dimensions numbered similarly.
rollcalls data frame, containing all data from the old perf21.dat file about bills. For a typical OCobject 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.
    PRE
    Proportional Reduction In Error.
    normvector1D
    First dimension of the unit normal vector, with all subsequent dimensions numbered similarly.
    midpoints
    The projection of the normal vector needed to get the midpoint.
dimensions integer, number of dimensions estimated.
eigenvalues A vector of roll call eigenvalues.
fits A vector of length 2 with the classic measures of fit, containing the percent correct classification and the APRE.

Author(s)

Keith Poole kpoole@ucsd.edu

Jeffrey Lewis jblewis@ucla.edu

James Lo jameslo@ucla.edu

Royce Carroll rcarroll@ucsd.edu

References

Keith Poole. 2000. 'Non-parametric Unfolding of Binary Choice Data.' Political Analysis, 8(3):211-237

Keith Poole. 2005. 'Spatial Models of Parliamentary Voting.' Cambridge: Cambridge University Press.

Keith Poole. http://voteview.ucsd.edu/

See Also

'plot.OCobject','summary.OCobject'.

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)
    result<-oc(sen90,dims=2,polarity=c(7,2))
    summary(result)
    plot(result) 


[Package oc version 0.04 Index]