R/read_SHeS_2010.R

In dosgillespie/hseclean: Health Survey Data Wrangling

#' Read Scottish Health Survey 2010
#'
#' Reads and does basic cleaning on the Scottish Health Survey 2010.
#'
#' The Scottish Health Survey is designed to yield a representative sample of the general population
#' living in private households in Scotland every year. 
#'
#'
#' MISSING VALUES
#'
#' \itemize{
#' \item -1 Not applicable: Used to signify that a particular variable did not apply to a given respondent
#' usually because of internal routing. For example, men in women only questions.
#' \item -2 Schedule not applicable: Used mainly for variables on the self-completions when the
#' respondent was not of the given age range, also used for children without legal guardians in the
#' home who could not participate in the nurse schedule.
#' \item -6 Schedule not obtained: Used to signify that a particular variable was not answered because the
#' respondent did not complete or agree to a particular schedule (i.e. nurse schedule or selfcompletions).
#' \item -8 Don't know, Can't say.
#' \item -9 No answer/ Refused
#' }
#'
#' @param root Character - the root directory.
#' @param file Character - the file path and name.
#' @importFrom data.table :=
#' @return Returns a data table. Note that:
#'
#' \itemize{
#' \item Missing data ("NA", "", "-1", "-2", "-6", "-7", "-9", "-90", "-90.0", "N/A") is replace with NA,
#'  -8 ("don't know") is also replaced with NA.
#' \item All variable names are converted to lower case.
#' \item Each data point is assigned a weight of 1 as there is no weight variable supplied.
#' \item A single sampling cluster is assigned.
#' \item The probabilistic sampling unit have the year appended to them.
#' }
#' @export
#'
#' @examples
#'
#' \dontrun{
#'
#' data_2010 <- read_SHeS_2010("X:/", 
#' "ScHARR/PR_Tobacco_mup/Data/Scottish Health Survey/SHeS 2010/UKDA-6987-tab/tab/shes10i_v4.tab")
#'
#' }
#'
read_SHeS_2010 <- function(
  root = c("X:/", "/Volumes/Shared/"),
  file = 
    "ScHARR/PR_Tobacco_mup/Data/Scottish Health Survey/SHeS 2010/UKDA-6987-tab/tab/shes10i_v4.tab"
) {
  
  data <- data.table::fread(
    paste0(root[1], file),
    na.strings = c("NA", "", "-1", "-2", "-6", "-7", "-8", "-9", "-90", "-90.0", "N/A")
  )
  
  data.table::setnames(data, names(data), tolower(names(data)))
  
  alc_vars <- Hmisc::Cs(
    # alc_drink_now_allages
    dnoft, dnnow, dnany, dnevr,
    # alc_sevenday_adult (heaviest day)
    d7day, d7many,
    nberqhp7, l7ncodeq, nberqlg, nberqsm, 
    #nberqbt7,
    sberqhp7, l7scodeq, sberqlg, sberqsm, 
    #sberqbt7,
    w250gl7, w175gl7, w125gl7, w125bl7,
    d7typ1, d7typ2, d7typ3, d7typ4, d7typ5, d7typ6,
    sherqgs7, spirqme7,
    popscl7, popsbl7, poplbl7,
    drnksame, whichday,
    # alc_weekmean_adult
    nbeer, sbeer, spirits, sherry, wine, pops03,
    nbeerm1, nbeerm2, nbeerm3, nbeerm4,
    nbeerq1, nbeerq2, nbeerq3, nberqbt,
    sbeerm1, sbeerm2, sbeerm3, sbeerm4,
    sbeerq1, sbeerq2, sbeerq3, sbeerq4,
    #sberqbt,
    wqglz1, wqglz2, wqglz3, q250glz, q175glz, q125glz, wqbt, wineq,
    sherryq, spiritsq,
    popsm031, popsm032, popsm033, popsq031, popsq032, popsq033,
    
    # to compare SHeS calcs with our estimates of weekly units
    nberwu, sberwu, spirwu, sherwu, winewu, popswu, drating,
    
    #self-completed 
    dwin08q0, dwin08q2, dwin08q3, dwin08q4, dshryq08, dspiritq, 
    dsbeerq0, dsbeerq2, dsbeerq3, dnbeerq0, dnbeerq2, dnbeerq3,
    dpop08q0, dpop08q2, dpop08q3,
    
    #self-completed frequency
    dpops08, dwine08, dshery08, dspirits, dsbeer, dnbeer
    
    #wineq, wqbt, wqgl, nberf, nberqhp, sberqhp, sberf, spirf, spirqme, sherf, sherqgs, winef,
    #win250g, win175g, win125g, win125b, popsf, popsqlb, popsqsb, popsqsc, nberqsm7, nberqlg7,
    #sberqsm7, sberqlg7
  )
  
  smk_vars <- Hmisc::Cs(startsmk, endsmoke, smokyrs, dcigage, smkevr, cignow, cigwday,
                        cigwend, cigevr, cigregs)
  
  health_vars <- paste0("compm", 1:14)
  
  other_vars <- Hmisc::Cs(
    
    psu,
    strata, # stratification unit
    int10wt, # individual weight after calibration
    cint10wt, # Child weight after calibration
    
    eqv5, eqvinc,
    
    # Education
    educend,
    hedqul08, # Highest educational qualification - revised 2008
    
    # Occupation
    nssec3, nssec8,    
    nactiv09, econac08,
    
    # Family
    maritalg,
    
    # demographic
    age,
    ethnic09,
    simd5_sg, simd5_rp,
    sex,
    
    # how much they weigh
    htval, wtval
    
  )
  
  
  names <- c(other_vars, health_vars, alc_vars, smk_vars)
  
  names <- tolower(names)
  
  data <- data[ , names, with = F]
  
  data.table::setnames(data,
           
           c("simd5_rp", "strata", "ethnic09", "eqv5", "eqvinc", "econac08",
             "cigregs",
             "w250gl7", "w175gl7", "w125gl7", "w125bl7",
             "popscl7", "popsbl7", "poplbl7",
             "l7scodeq", "sberqlg", "sberqsm",
             "l7ncodeq", "nberqlg", "nberqsm",
             
             # amount drunk on one day
             "nberqbt",
             "pops03", "popsm031", "popsm032", "popsm033", "popsq031", "popsq032", "popsq033",
             
             #self-completed 
             "dnbeerq0", "dnbeerq2", "dnbeerq3",
             "dsbeerq0", "dsbeerq2", "dsbeerq3",              
             "dwin08q0", "dwin08q2", "dwin08q3", "dwin08q4", "dshryq08", "dspiritq", 
             "dpop08q0", "dpop08q2", "dpop08q3",
             #self-completed frequency
             "dpops08", "dwine08", "dshery08", "dspirits", "dsbeer", "dnbeer"),
           
           c("simd", "cluster", "ethnicity_raw", "eqv5_15", "eqvinc_15", "econac12",
             "cigreg",
             "wgls250ml", "wgls175ml", "wgls125ml", "wbtlgz",
             "popsqsmc7", "popsqsm7", "popsqlg7",
             "sberqpt7", "sberqlg7", "sberqsm7",
             "nberqpt7", "nberqlg7", "nberqsm7",
             
             # amount drunk on one day
             "nbeerq4", 
             "pops", "popsly11", "popsly12", "popsly13", "popsq111", "popsq112", "popsq113",
             
             #self-completed
             "scnbeeq1", "scnbeeq3", "scnbeeq2",
             "scsbeeq1", "scsbeeq3", "scsbeeq2",
             "scwineq3", "scwineq2", "scwineq1", "scwineq4", "scsherrq", "scspirq",
             "scpopsq3", "scpopsq2", "scpopsq1",
             #self-completed frequency
             "scpops", "scwine", "scsherry", "scspirit", "scsbeer", "scnbeer"
           ))
  
  # Tidy survey weights
  data[ , wt_int := int10wt]
  data[age < 16, wt_int := cint10wt]
  data[ , cint10wt := NULL]
  
  # Set PSU and cluster
  data[ , psu := paste0("2010_", psu)]
  data[ , cluster := paste0("2010_", cluster)]
  
  data[ , year := 2010]
  data[ , country := "Scotland"]
  
  return(data[])
}