R Dataset / Package pscl / politicalInformation

On this R-data statistics page, you will find information about the politicalInformation data set which pertains to Interviewer ratings of respondent levels of political information. The politicalInformation data set is found in the pscl R package. You can load the politicalInformation data set in R by issuing the following command at the console data("politicalInformation"). This will load the data into a variable called politicalInformation. If R says the politicalInformation data set is not found, you can try installing the package by issuing this command install.packages("pscl") and then attempt to reload the data with the library() command. If you need to download R, you can go to the R project website. You can download a CSV (comma separated values) version of the politicalInformation R data set. The size of this file is about 104,140 bytes.

Interviewer ratings of respondent levels of political information

Description

Interviewers administering the 2000 American National Election Studies assigned an ordinal rating to each respondent's "general level of information" about politics and public affairs.

Usage

data(politicalInformation)

Format

A data frame with 1807 observations on the following 8 variables.

y

interviewer rating, a factor with levels Very Low Fairly Low Average Fairly High Very High

collegeDegree

a factor with levels No Yes

female

a factor with levels No Yes

age

a numeric vector, respondent age in years

homeOwn

a factor with levels No Yes

govt

a factor with levels No Yes

length

a numeric vector, length of ANES pre-election interview in minutes

id

a factor, unique identifier for each interviewer

Details

Seven respondents have missing data on the ordinal interviewer rating. The covariates age and length also have some missing data.

Source

The National Election Studies (www.electionstudies.org). THE 2000 NATIONAL ELECTION STUDY [dataset]. Ann Arbor, MI: University of Michigan, Center for Political Studies [producer and distributor].

References

Jackman, Simon. 2009. Bayesian Analysis for the Social Sciences. Wiley: Hoboken, New Jersey.

Examples

data(politicalInformation)table(politicalInformation$y,exclude=NULL)op <- MASS::polr(y ~ collegeDegree + female + log(age) + homeOwn + govt + log(length),
 data=politicalInformation,
 Hess=TRUE,
 method="probit")

Dataset imported from https://www.r-project.org.

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