# oc {oc}

### 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.

### Values

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.

### 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/ "> 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 <a href="http://www.voteview.com<br /> " title="www.voteview.com<br /> ">www.voteview.com<br /> </a> data(sen90) summary(sen90) result<-oc(sen90,dims=2,polarity=c(7,2)) summary(result) plot(result)

Documentation reproduced from package oc, version 0.93. License: GPL-2