Recoding data from the British Election Study

The following makes use of the memisc package. You may need to install it from CRAN 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)

Loading required package: lattice
Loading required package: MASS

Attaching package: 'memisc'

The following objects are masked from 'package:stats':

    contr.sum, contr.treatment, contrasts

The following object is masked from 'package:base':

    as.array

The following code picks up with the British Election Study data of the previous script. We use the data file created earlier. For convenience, this data file is available for download from here: Social Science Surveys

load("BES-1983-classvot.RData")

# This code collapses the categories of the vote variable into just four:
BES.1983.classvot <- within(BES.1983.classvot,{
    vote.new <- vote
    vote.new[vote %in% 3:5]        <- 3
    vote.new[vote %in% c(6:10,97)] <- 4
})
# Checking the result:
codebook(BES.1983.classvot$vote.new)

================================================================================

   BES.1983.classvot$vote.new '[IF VOTED] PARTY VOTED FOR'

--------------------------------------------------------------------------------

   Storage mode: double
   Measurement: nominal
   Missing values: 95, 96, 97, 98, 99

   Values and labels         N Valid Total
                                          
    0   'SKIPPED'          660  17.1  16.7
    1   'CON'             1432  37.1  36.2
    2   'LAB'              937  24.3  23.7
    3   'ALLIANCE'         788  20.4  19.9
    4   'LIB'               44   1.1   1.1
    5   'SOCIAL  DEMOCR'     0   0.0   0.0
    6   'SNP'                0   0.0   0.0
    7   'PLAID   CYMRU'      0   0.0   0.0
    8   'ECOLOGY PARTY'      0   0.0   0.0
    9   'NATNL   FRONT'      0   0.0   0.0
   10   'COMNIST PARTY'      0   0.0   0.0
   95 M 'REFUSED'           92         2.3
   97 M 'OTHER   PARTY'      2         0.1

# It is somewhat more convenient to use the 'recode()' function from the
# 'memisc' package:
BES.1983.classvot <- within(BES.1983.classvot,{
    vote.new <- recode(vote,
                       3 <- 3:5,
                       4 <- c(6:10,97),
                       otherwise="copy"
                       )
})
# Checking the result:
codebook(BES.1983.classvot$vote.new)

================================================================================

   BES.1983.classvot$vote.new '[IF VOTED] PARTY VOTED FOR'

--------------------------------------------------------------------------------

   Storage mode: double
   Measurement: nominal
   Missing values: 95, 96, 97, 98, 99

   Values and labels     N Valid Total
                                      
    0   'SKIPPED'      660  17.1  16.7
    1   'CON'         1432  37.1  36.2
    2   'LAB'          937  24.3  23.7
    3   'ALLIANCE'     788  20.4  19.9
    4   'LIB'           46   1.2   1.2
   95 M 'REFUSED'       92         2.3

# Since 'BES.1983.classvot' is not a data frame, but a "data.set" object, we can
# provide value labels while recoding:
BES.1983.classvot <- within(BES.1983.classvot,{
    vote.new <- recode(vote,
                       Conservative  = 1 <- 1,
                       Labour        = 2 <- 2,
                       Alliance      = 3 <- 3:5,
                       Other         = 4 <- c(6:10,97),
                       "Didn't vote" = 5 <- 0,
                       DK            = 8 <- 98,
                       Refused       = 9 <- 95)
    missing.values(vote.new) <- c(5,9)
})
# Checking the result:
codebook(BES.1983.classvot$vote.new)

Warning in recode(vote, Conservative = 1 <- 1, Labour = 2 <- 2, Alliance = 3 <- 3:5, :
recoding 8 <- 98 has no consequences

================================================================================

   BES.1983.classvot$vote.new '[IF VOTED] PARTY VOTED FOR'

--------------------------------------------------------------------------------

   Storage mode: double
   Measurement: nominal
   Missing values: 5, 9

   Values and labels      N Valid Total
                                       
   1   'Conservative'  1432  44.7  36.2
   2   'Labour'         937  29.3  23.7
   3   'Alliance'       788  24.6  19.9
   4   'Other'           46   1.4   1.2
   5 M 'Didn't vote'    660        16.7
   8   'DK'               0   0.0   0.0
   9 M 'Refused'         92         2.3