The American National Election Studies are one of the most important sources of data for political scientists. anesr provides easy access to ANES data for R users. anesr includes tidy versions of all ANES pilot and time series studies as compact, rda objects. Once the package is installed and loaded, any dataset can be accessed using the data() function. anesr also includes documentation for some studies in tidy format. Documentation files include descriptions, coding, and marginals or summary statistics for all variables in the dataset.

To install anesr, use the install_github function from the devtools package:

library(devtools)
install_github("jamesmartherus/anesr")

library(anesr)

data(package="anesr") #View a list of available datasets

data(timeseries_cum) #Load Time Series Cumulative File (1948-2016)
data(timeseries_cum_doc) #Load documentation for the Time Series Cumulative File

data(pilot_2018) #Load 2018 Pilot Study

By using these data, you agree to the terms of use established by the ANES:

• Use these datasets solely for research or statistical purposes and not for investigation of specific survey respondents.
• Make no use of the identity of any survey respondent(s) discovered intentionally or inadvertently, and to advise ANES of any such discovery ([email protected])
• Cite ANES data and documentation in your work that makes use of the data and documentation. Authors of publications based on ANES data should send citations of their published works to ANES for inclusion in our bibliography of related publications.
• You acknowledge that the original collector of the data, ANES, and the relevant funding agency/agencies bear no responsibility for use of the data or for interpretations or inferences based upon such uses.

ANES is not responsible for any errors in these datasets - any mistakes are mine.

• The ANES is administered through a collaboration between Stanford University and the University of Michigan with funding by the National Science Foundation.
• anesr is inspired by Kieran Healy's excellent gssr package. I used Kieran's SDA parser to generate documentation files. You should follow Kieran on Twitter.