vote92 | R Documentation |
Survey data containing self-reports of vote choice in the 1992 U.S. Presidential election, with numerous covariates, from the 1992 American National Election Studies.
data(vote92)
A data frame with 909 observations on the following 10 variables.
vote
a factor with levels Perot
Clinton
Bush
dem
a numeric vector, 1 if the respondent reports identifying with the Democratic party, 0 otherwise.
rep
a numeric vector, 1 if the respondent reports identifying with the Republican party, 0 otherwise
female
a numeric vector, 1 if the respondent is female, 0 otherwise
persfinance
a numeric vector, -1 if the respondent reports that their personal financial situation has gotten worse over the last 12 months, 0 for no change, 1 if better
natlecon
a numeric vector, -1 if the respondent reports that national economic conditions have gotten worse over the last 12 months, 0 for no change, 1 if better
clintondis
a numeric vector, squared difference between respondent's self-placement on a scale measure of political ideology and the respondent's placement of the Democratic candidate, Bill Clinton
bushdis
a numeric vector, squared ideological distance of the respondent from the Republican candidate, President George H.W. Bush
perotdis
a numeric vector, squared ideological distance of the respondent from the Reform Party candidate, Ross Perot
These data are unweighted. Refer to the original data source for weights that purport to correct for non-representativeness and non-response.
Alvarez, R. Michael and Jonathan Nagler. 1995. Economics, issues and the Perot candidacy: Voter choice in the 1992 Presidential election. American Journal of Political Science. 39:714-44.
Miller, Warren E., Donald R. Kinder, Steven J. Rosenstone and the National Election Studies. 1999. National Election Studies, 1992: Pre-/Post-Election Study. Center for Political Studies, University of Michigan: Ann Arbor, Michigan.
Inter-University Consortium for Political and Social Research. Study Number 1112. http://dx.doi.org/10.3886/ICPSR01112.
Jackman, Simon. 2009. Bayesian Analysis for the Social Sciences. Wiley: Hoboken, New Jersey. Examples 8.7 and 8.8.
data(vote92) summary(vote92)