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pscl (version 0.97)

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

0.97

License

GPL-2

Maintainer

Simon Jackman

Last Published

January 31st, 2024

Functions in pscl (0.97)

predict.ideal

predicted probabilities from an ideal object
constrain.items

constrain item parameters in analysis of roll call data
hurdle

Hurdle Models for Count Data Regression
extractRollCallObject

return the roll call object used in fitting an ideal model
presidentialElections

elections for U.S. President, 1932-2004, by state
pR2

compute various pseduo-R2 measures
summary.rollcall

summarize a rollcall object
state.info

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

Applications to a Political Science PhD Program
sc9497

votes from the United States Supreme Court, from 1994-1997
predprob.glm

Predicted Probabilties for GLM Fits
zeroinfl

Zero-inflated Count Data Regression
predprob.ideal

predicted probabilities from fitting ideal to rollcall data
hurdle.control

Control Parameters for Hurdle Count Data Regression
bioChemists

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

Monte Carlo estimate of pi (3.14159265...)
plot.predict.ideal

plot methods for predictions from ideal objects
ideal

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

compute and optionally plot beta HDRs
AustralianElections

elections to Australian House of Representatives, 1949-2004
dropRollCall

drop user-specified elements from a rollcall object
postProcess

remap MCMC output via affine transformations
rollcall

create an object of class rollcall
computeMargins

add information about voting outcomes to a rollcall object
s109

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

Table of Actual Outcomes against Predicted Outcomes for discrete data models
seatsVotes

A class for creating seats-votes curves
readKH

read roll call data in Poole-Rosenthal KH format
odTest

likelihood ratio test for over-dispersion in count data
idealToMCMC

convert an object of class ideal to a coda MCMC object
vuong

Vuong's non-nested hypothesis test
predict.zeroinfl

Methods for zeroinfl Objects
dropUnanimous

drop unanimous votes from rollcall objects and matrices
igamma

inverse-Gamma distribution
unionDensity

cross national rates of trade union density
zeroinfl.control

Control Parameters for Zero-inflated Count Data Regression
plot.seatsVotes

plot seats-votes curves
tracex

trace plot of MCMC iterates, posterior density of legislators' ideal points
ca2006

California Congressional Districts in 2006
convertCodes

convert entries in a rollcall matrix to binary form
predprob

compute predicted probabilities from fitted models
prussian

Prussian army horse kick data
hurdletest

Testing for the Presence of a Zero Hurdle
constrain.legis

constrain legislators' ideal points in analysis of roll call data
summary.ideal

summary of an ideal object
predict.hurdle

Methods for hurdle Objects
ntable

nicely formatted tables
vectorRepresentation

convert roll call matrix to series of vectors
plot.ideal

plots an ideal object
partycodes

political parties appearing in the U.S. Congress
absentee

Absentee and Machine Ballots in Pennsylvania State Senate Races