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pscl (version 1.5.5.1)

Political Science Computational Laboratory

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.packages('pscl')

Monthly Downloads

34,594

Version

1.5.5.1

License

GPL-2

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Repository

http://github.com/atahk/pscl

Maintainer

Simon Jackman

Last Published

May 10th, 2023

Functions in pscl (1.5.5.1)

AustralianElectionPolling

Political opinion polls in Australia, 2004-07

Voter turnout experiment, using Rock The Vote ads

California Congressional Districts in 2006

constrain.items

constrain item parameters in analysis of roll call data

Table of Actual Outcomes against Predicted Outcomes for discrete data models

convert entries in a rollcall matrix to binary form

Hurdle Models for Count Data Regression

Control Parameters for Hurdle Count Data Regression

drop unanimous votes from rollcall objects and matrices

constrain.legis

constrain legislators' ideal points in analysis of roll call data

add information about voting outcomes to a rollcall object

extractRollCallObject

return the roll call object used in fitting an ideal model

drop user-specified elements from a rollcall object

nicely formatted tables

convert an object of class ideal to a coda MCMC object

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

political parties appearing in the U.S. Congress

rollcall object, National Journal key votes of 2007

inverse-Gamma distribution

compute various pseudo-R2 measures

Testing for the Presence of a Zero Hurdle

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

likelihood ratio test for over-dispersion in count data

plot.predict.ideal

plot methods for predictions from ideal objects

plots an ideal object

predicted probabilities from an ideal object

politicalInformation

Interviewer ratings of respondent levels of political information

Methods for hurdle Objects

plot.seatsVotes

plot seats-votes curves

predict.zeroinfl

Methods for zeroinfl Objects

remap MCMC output via affine transformations

Predicted Probabilities for GLM Fits

compute predicted probabilities from fitted models

create an object of class rollcall

Prussian army horse kick data

A class for creating seats-votes curves

Monte Carlo estimate of pi (3.14159265...)

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

presidentialElections

elections for U.S. President, 1932-2016, by state

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

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

read roll call data in Poole-Rosenthal KH format

predicted probabilities from fitting ideal to rollcall data

Vuong's non-nested hypothesis test

summary of an ideal object

Zero-inflated Count Data Regression

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

cross national rates of trade union density

zeroinfl.control

Control Parameters for Zero-inflated Count Data Regression

summary.rollcall

summarize a rollcall object

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

vectorRepresentation

convert roll call matrix to series of vectors

Batting Averages for 18 major league baseball players, 1970

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

Absentee and Machine Ballots in Pennsylvania State Senate Races

Applications to a Political Science PhD Program

AustralianElections

elections to Australian House of Representatives, 1949-2016

UKHouseOfCommons

1992 United Kingdom electoral returns

compute and optionally plot beta HDRs