Raking 2016 American National Election Study data¶
The following makes use of the survey package. You may need to install it from
CRAN using the code
install.packages("survey") if you want to run this on your computer. (The
package is already installed on the notebook container, however.)
Loading required package: grid Loading required package: Matrix Loading required package: survival Attaching package: 'survey' The following object is masked from 'package:graphics': dotchart
Here we rake the sample design object by recalled vote in 2012 and vote in 2016
load("anes-2016-vprevote-design.RData") load("popl-results.RData") anes_2016_prevote_desgn_rake <- rake( anes_2016_vprevote_desgn,list(~recall12,~vote16), population=list(pop.recall12,pop.vote16), control=list(maxit=20))
Of course, the marginal distributions of the vote in 2012 and the vote in 2016 are no longer estimated, so that standard errors now vanish.
mean SE recall12Obama 28.01970 0 recall12Romney 25.90182 0 recall12Other 0.95053 0 recall12No vote 45.12795 0
mean SE vote16Clinton 26.3355 0 vote16Trump 25.1883 0 vote16Other 3.1324 0 vote16No vote 45.3439 0
The actual percentage of non-voters in 2016 is obviously much higher than the one estimated from the sample, be it post-stratified or not.
We save the raked data for later use.
- R file: raking-ANES2016.R
- Rmarkdown file: raking-ANES2016.Rmd
- Jupyter notebook file: raking-ANES2016.ipynb
- Interactive version of the Jupyter notebook (shuts down after 60s):
- Interactive version of the Jupyter notebook (sign in required):