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pscl (version 1.4.9)

Political Science Computational Laboratory, Stanford University

Description

Bayesian analysis of item-response theory (IRT) models, roll call analysis; computing highest density regions; maximum likelihood estimation of zero-inflated and hurdle models for count data; goodness-of-fit measures for GLMs; data sets used in writing and teaching at the Political Science Computational Laboratory; seats-votes curves.

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Install

install.packages('pscl')

Monthly Downloads

25,438

Version

1.4.9

License

GPL-2

Maintainer

Last Published

March 29th, 2015

Functions in pscl (1.4.9)

AustralianElectionPolling

Political opinion polls in Australia, 2004-07

convert an object of class ideal to a coda MCMC object

Control Parameters for Hurdle Count Data Regression

predict.zeroinfl

Methods for zeroinfl Objects

convert entries in a rollcall matrix to binary form

political parties appearing in the U.S. Congress

Absentee and Machine Ballots in Pennsylvania State Senate Races

rollcall object, National Journal key votes of 2007

plots an ideal object

UKHouseOfCommons

1992 United Kingdom electoral returns

Hurdle Models for Count Data Regression

predicted probabilities from fitting ideal to rollcall data

constrain.legis

constrain legislators' ideal points in analysis of roll call data

summary of an ideal object

drop unanimous votes from rollcall objects and matrices

plot.predict.ideal

plot methods for predictions from ideal objects

remap MCMC output via affine transformations

compute predicted probabilities from fitted models

Batting Averages for 18 major league baseball players, 1970

add information about voting outcomes to a rollcall object

nicely formatted tables

drop user-specified elements from a rollcall object

Monte Carlo estimate of pi (3.14159265...)

Reports of voting in the 1992 U.S. Presidential election.

Zero-inflated Count Data Regression

summary.rollcall

summarize a rollcall object

Prussian army horse kick data

extractRollCallObject

return the roll call object used in fitting an ideal model

California Congressional Districts in 2006

likelihood ratio test for over-dispersion in count data

compute and optionally plot beta HDRs

Methods for hurdle Objects

Applications to a Political Science PhD Program

Voter turnout experiment, using Rock The Vote ads

compute various pseudo-R2 measures

analysis of educational testing data and roll call data with IRT models, via Markov chain Monte Carlo methods

predicted probabilities from an ideal object

Vuong's non-nested hypothesis test

vectorRepresentation

convert roll call matrix to series of vectors

AustralianElections

elections to Australian House of Representatives, 1949-2007

constrain.items

constrain item parameters in analysis of roll call data

article production by graduate students in biochemistry Ph.D. programs

create an object of class rollcall

plot.seatsVotes

plot seats-votes curves

rollcall object, 109th U.S. Senate (2005-06).

A class for creating seats-votes curves

Predicted Probabilties for GLM Fits

Table of Actual Outcomes against Predicted Outcomes for discrete data models

cross national rates of trade union density

inverse-Gamma distribution

trace plot of MCMC iterates, posterior density of legislators' ideal points

presidentialElections

elections for U.S. President, 1932-2012, by state

votes from the United States Supreme Court, from 1994-1997

Testing for the Presence of a Zero Hurdle

politicalInformation

Interviewer ratings of respondent levels of political information

zeroinfl.control

Control Parameters for Zero-inflated Count Data Regression

U.S. Senate vote on the use of force against Iraq, 2002.

read roll call data in Poole-Rosenthal KH format

information about the American states needed for U.S. Congress