#' # Poststratification of 2016 American National Election Study data

#' The following data file was created in an earlier script / notebook.

load("anes-2016-prevote.RData")

#' There must not be any missing values in the stratifying variables.

anes_2016_vprevote <- subset(anes_2016_prevote,
                                    vote16 != "Inap" &
                                    recall12 != "Inap"
                                    )

#' In order to make poststratification possible, we need to make sure that the
#' levels of the stratification variables match the population
#' information. Therefore we relabel the variables "recall12" and "vote16".

#' The following makes use of the *memisc* package. You may need to install it from
#' [CRAN](https://cran.r-project.org/package=memisc) using the code
#' `install.packages("memisc")` if you want to run this on your computer. (The
#' package is already installed on the notebook container, however.)

library(memisc)

anes_2016_vprevote <- within(anes_2016_vprevote,{
    recall12 <- recall12[,drop=TRUE]
    vote16 <- vote16[,drop=TRUE]
    recall12 <- relabel(recall12,"Did not vote"="No vote")
    vote16 <- relabel(vote16,
                      "Will not vote/Not registered"="No vote")
})
save(anes_2016_vprevote,file="anes-2016-vprevote.RData")

#' Finally, we set up a survey design object. The following makes use of the *survey* package. You may need to install it from [CRAN](https://cran.r-project.org/package=survey) 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.)

library(survey)

anes_2016_vprevote_desgn <- svydesign(id = ~psu_f2f,
                                       strata = ~strat_f2f,
                                       weights = ~pre_w_f2f,
                                       data = anes_2016_vprevote,
                                       nest = TRUE)
save(anes_2016_vprevote_desgn,file="anes-2016-vprevote-design.RData")

#' We collect the electoral results of 2012 to prepare poststratification.

result.2012 = c(Obama  = 65915795,
                Romney = 60933504,
                # Other candidates are combined
                Other = sum(c(
                    Johson = 1275971,
                    Stein  =  469627,
                    Others =  490510
                )))

#' The number of non-voters is computed from the sum of the results and census
#' data on the population in voting age.

result.2012 <- c(result.2012,
                 "No vote" = 235248000 - sum(result.2012)) 

# Here we collect the results for 2016
result.2016 <- c(Clinton = 65853514,
                 Trump   = 62984828,
                 Other   = sum(c(
                    Johnson  = 4489341, 
                    Stein    = 1457218,
                    McMullin =  731991,
                    Others   = 1154084 
                 )))

result.2016 <- c(result.2016,
                 "No vote" = 250056000 - sum(result.2016))                 

#' The poststratification function expects population data to be in the form of
#' data frames:

pop.vote16 <- data.frame(
    vote16=names(result.2016),
    Freq=result.2016)

pop.recall12 <- data.frame(
    recall12=names(result.2012),
    Freq=result.2012/sum(result.2012)*sum(result.2016)
)

save(pop.recall12,pop.vote16,file="popl-results.RData")

#' We poststratify the sample design object by recalled vote in 2012

anes_2016_prevote_desgn_post <- postStratify(
    anes_2016_vprevote_desgn,~recall12,population=pop.recall12)

#' We compare the estimated percentages of 2012 votes:

100*svymean(~recall12,design=anes_2016_vprevote_desgn)

100*svymean(~recall12,design=anes_2016_prevote_desgn_post)

#' As should be expected, post-stratification eliminates the uncertainty about
#' 2012 votes. It also corrects for turnout overreporting.

#' We now compare the estimated percentages of 2016 votes

100*svymean(~vote16,design=anes_2016_vprevote_desgn)

100*svymean(~vote16,design=anes_2016_prevote_desgn_post)

#' The percentages of Clinton voters and Trump voters are closer after
#' poststratification.

#' We save the poststratified data for later use.

save(anes_2016_prevote_desgn_post,file="anes-2016-prevote-desgn-post.RData")