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pscl (version 1.5.2)

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')

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43,915

Version

1.5.2

License

GPL-2

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Repository

http://github.com/atahk/pscl

Maintainer

Last Published

October 10th, 2017

Functions in pscl (1.5.2)

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

California Congressional Districts in 2006

Applications to a Political Science PhD Program

compute and optionally plot beta HDRs

AustralianElectionPolling

Political opinion polls in Australia, 2004-07

AustralianElections

elections to Australian House of Representatives, 1949-2016

UKHouseOfCommons

1992 United Kingdom electoral returns

Absentee and Machine Ballots in Pennsylvania State Senate Races

Batting Averages for 18 major league baseball players, 1970

Voter turnout experiment, using Rock The Vote ads

drop user-specified elements from a rollcall object

extractRollCallObject

return the roll call object used in fitting an ideal model

add information about voting outcomes to a rollcall object

Hurdle Models for Count Data Regression

Control Parameters for Hurdle Count Data Regression

nicely formatted tables

likelihood ratio test for over-dispersion in count data

Table of Actual Outcomes against Predicted Outcomes for discrete data models

convert an object of class ideal to a coda MCMC object

inverse-Gamma distribution

plots an ideal object

plot.predict.ideal

plot methods for predictions from ideal objects

Monte Carlo estimate of pi (3.14159265...)

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

drop unanimous votes from rollcall objects and matrices

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

rollcall object, National Journal key votes of 2007

plot.seatsVotes

plot seats-votes curves

politicalInformation

Interviewer ratings of respondent levels of political information

create an object of class rollcall

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

predicted probabilities from an ideal object

predict.zeroinfl

Methods for zeroinfl Objects

Prussian army horse kick data

read roll call data in Poole-Rosenthal KH format

constrain.items

constrain item parameters in analysis of roll call data

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

remap MCMC output via affine transformations

Methods for hurdle Objects

predicted probabilities from fitting ideal to rollcall data

presidentialElections

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

zeroinfl.control

Control Parameters for Zero-inflated Count Data Regression

convert entries in a rollcall matrix to binary form

constrain.legis

constrain legislators' ideal points in analysis of roll call data

compute various pseudo-R2 measures

political parties appearing in the U.S. Congress

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

cross national rates of trade union density

Vuong's non-nested hypothesis test

Zero-inflated Count Data Regression

compute predicted probabilities from fitted models

Predicted Probabilties for GLM Fits

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

A class for creating seats-votes curves

vectorRepresentation

convert roll call matrix to series of vectors

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

summary of an ideal object

summary.rollcall

summarize a rollcall object