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.