#' # Constructing a survey design object from data of the 2016 American Election   Study.

#' 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)

#' The the code makes used of the data file "`anes_timeseries_2016.sav`", which is not included in the supporting material. In order to 
#' obtain this data file (and run this notebook successufully), you need to download them from 
#' the [ANES website for 2016](https://electionstudies.org/data-center/2016-time-series-stud/) and upload them to the virtual
#' machine that runs this notebook. To do this, 
#'
#' 1. pull down the "File" menu item and select "Open"
#' 2. An overview of the folder that contains the notebook opens. 
#' 3. The folder view has a button labelled "Upload". Use this to upload the file that you downloaded from the ANES website.
#'
#' Note that the uploaded data will disappear, once you "Quit" the notebook (and the Jupyter instance).

anes_2016_sav <- spss.file("anes_timeseries_2016.sav")

#' Loading a subset: Only pre-election waves and only
#' face-to-face interviews

anes_2016_pre_work_ds <- subset(anes_2016_sav,
                                V160501 == 1,
                                select=c(
                                # According to docs, these are the
                                # sample weights for the
                                # face-to-face component
                                pre_w_f2f     = V160101f,
                                # Face-to-face strata    
                                strat_f2f     = V160201f,
                                psu_f2f       = V160202f,
                                pre_voted12   = V161005,
                                pre_recall12  = V161006,
                                pre_voted     = V161026,
                                pre_vote      = V161027,
                                pre_intov     = V161030,
                                pre_voteint   = V161031#,
                           ))

library(magrittr) # For the '%<>%' operator

anes_2016_pre_work_ds %<>% within({
    # Setting up recalled votes of 2012
    # Since a "default" value for the remaining conditions
    # is used, we use 'check.xor = FALSE' to avoid warnings.
    recall12 <- cases(
        'Did not vote' = 9 <- pre_voted12  == 2,
        'Obama'        = 1 <- pre_recall12 == 1,
        'Romney'       = 2 <- pre_recall12 == 2,
        'Other'        = 3 <- pre_recall12 == 5,
        'Inap'         = 99 <- TRUE, check.xor = FALSE
    )
    # Early voters 
    vote16_1 <- cases(
        'Clinton' = 1 <- pre_voted == 1 & pre_vote == 1,
        'Trump'   = 2 <- pre_voted == 1 & pre_vote == 2,
        'Other'   = 3 <- pre_voted == 1 & pre_vote %in% 3:5,
        'Inap'    = 99 <- TRUE, check.xor = FALSE)
    # Vote intentions
    vote16 <- cases(
        'Clinton' = 1 <- pre_intov == 1 & pre_voteint == 1,
        'Trump'   = 2 <- pre_intov == 1 & pre_voteint == 2,
        'Other'   = 3 <- pre_intov == 1 & pre_voteint %in% 3:6,
        'Will not vote/Not registered' = 8 <- pre_intov %in% c(-1,2),
        'Inap'    = 99 <- TRUE, check.xor = FALSE)
    vote16[] <- ifelse(vote16 == 99 & vote16_1 != 99,
                       vote16_1,
                       vote16)
    measurement(pre_w_f2f) <- "ratio"
})

anes_2016_prevote <- as.data.frame(anes_2016_pre_work_ds)
save(anes_2016_prevote,file="anes-2016-prevote.RData")

#Unweighted crosstable
xtabs(~ vote16 + recall12,
      data=anes_2016_prevote)

#' 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_prevote_desgn <- svydesign(id = ~psu_f2f,
                                     strata = ~strat_f2f,
                                     weights = ~pre_w_f2f,
                                     data = anes_2016_prevote,
                                     nest = TRUE)
anes_2016_prevote_desgn

#' In order to later make use of the survey design object, we save it into a file.

save(anes_2016_prevote_desgn,file="anes-2016-prevote-desgn.RData")

#' We reduce the digits after dot ...

ops <- options(digits=2)
(tab <- svytable(~ vote16 + recall12,
                 design = anes_2016_prevote_desgn))

#' and drop counts of non-valid responses before
#' we compute percentages.

percentages(vote16 ~ recall12, data=tab[-6,-5])

options(ops) # To undo the change in the options.

#' Here we compute a *F*-test of independence with the table, which uses the
#' Rao-Scott second-order correction with a Satterthwaite approximation of the
#' denominator degrees of freedom is used.

summary(tab)

#' The more conventional Pearson-Chi-squared test adjusted with a design-effect
#' estimate is obtained by a slight modification.

summary(tab, statistic="Chisq")