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pscl (version 1.03.3)

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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Version

Install

install.packages('pscl')

Monthly Downloads

27,194

Version

1.03.3

License

GPL-2

Maintainer

Simon Jackman

Last Published

January 19th, 2010

Functions in pscl (1.03.3)

AustralianElections

elections to Australian House of Representatives, 1949-2004

Voter turnout experiment, using Rock The Vote ads

California Congressional Districts in 2006

summary of an ideal object

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

plot.seatsVotes

plot seats-votes curves

Predicted Probabilties for GLM Fits

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

Absentee and Machine Ballots in Pennsylvania State Senate Races

Hurdle Models for Count Data Regression

constrain.legis

constrain legislators' ideal points 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

plots an ideal object

Methods for hurdle Objects

vectorRepresentation

convert roll call matrix to series of vectors

inverse-Gamma distribution

likelihood ratio test for over-dispersion in count data

drop unanimous votes from rollcall objects and matrices

Control Parameters for Hurdle Count Data Regression

drop user-specified elements from a rollcall object

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

Applications to a Political Science PhD Program

constrain.items

constrain item parameters in analysis of roll call data

politicalInformation

Interviewer ratings of respondent levels of political information

extractRollCallObject

return the roll call object used in fitting an ideal model

nicely formatted tables

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

Prussian army horse kick data

Testing for the Presence of a Zero Hurdle

remap MCMC output via affine transformations

presidentialElections

elections for U.S. President, 1932-2004, by state

add information about voting outcomes to a rollcall object

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

summary.rollcall

summarize a rollcall object

predict.zeroinfl

Methods for zeroinfl Objects

plot.predict.ideal

plot methods for predictions from ideal objects

compute and optionally plot beta HDRs

predicted probabilities from an ideal object

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

create an object of class rollcall

compute various pseduo-R2 measures

read roll call data in Poole-Rosenthal KH format

cross national rates of trade union density

Vuong's non-nested hypothesis test

Zero-inflated Count Data Regression

political parties appearing in the U.S. Congress

A class for creating seats-votes curves

Monte Carlo estimate of pi (3.14159265...)

compute predicted probabilities from fitted models

predicted probabilities from fitting ideal to rollcall data

zeroinfl.control

Control Parameters for Zero-inflated Count Data Regression

Batting Averages for 18 major league baseball players, 1970

convert an object of class ideal to a coda MCMC object