R/ez.imp.R

In NicolasStefaniak/easieR: easieR: A GUI R metapackage.

ez.imp <-
  function(data=NULL, imp="median", ord=NULL, id=NULL, noms=NULL, info=T){
    # data : data.frame
    # imp : one among "rm", "mean", "median", "amelia"
    # ord : if imp is amelia, names of ordinal variables
    # id : if imp is amelia, names of id variables
    # noms : if imp is amelia, names of nominal variables

    packages<-c('Amelia',  'svDialogs')
    try(lapply(packages, library, character.only=T), silent=T)->test2
    if(class(test2)== 'try-error') return(ez.install())
    .e <- environment()
    if(is.null(data)) { dial<-T
    data<-choix.data(data=data, info=info, nom=T)
    if(length(data)==0) return(NULL)
    nom<-data[[1]]
    data<-data[[2]]
    } else {dial<-F
    deparse(substitute(data))->nom  }
    nom<-paste0(nom,".complet")

    if(dial || imp%in% c(.dico[["txt_do_nothing_keep_all_obs"]], .dico[["txt_delete_observations_with_missing_values"]], .dico[["txt_replace_by_mean"]],
                         .dico[["txt_replace_by_median"]],.dico[["txt_multiple_imputation_amelia"]],"rien","rm", "mean","median", "amelia") == FALSE){
      writeLines(.dico[["ask_missing_value_treatment"]])
      print(sapply(data, function(x) sum(length(which(is.na(x))))) )

      imp<- dlgList(c(.dico[["txt_do_nothing_keep_all_obs"]], .dico[["txt_delete_observations_with_missing_values"]], .dico[["txt_replace_by_mean"]],
                      .dico[["txt_replace_by_median"]],.dico[["txt_multiple_imputation_amelia"]]), preselect=FALSE, multiple = FALSE, title=.dico[["txt_missing_values_treatment"]])$res
      if(length(imp)==0){
        return(NULL)
      }
    }
    if(length(imp)==0) return(NULL)
    if(imp == .dico[["txt_do_nothing_keep_all_obs"]] || imp=="rien") return(data)
    if(imp== .dico[["txt_delete_observations_with_missing_values"]]|| imp=="rm"){
      data<-data[complete.cases(data),]
      if(dial)  assign(nom, data, envir=.GlobalEnv)
    }
    if(imp==.dico[["txt_replace_by_mean"]]|| imp=="mean"){
      for(i in 1 : length(data)) {data[which(is.na(data[,i])),i]<-mean(data[,i], na.rm=T)}
      if(dial)  assign(nom, data, envir=.GlobalEnv)
    }
    if(imp== .dico[["txt_replace_by_median"]]|| imp=="median"){
      for(i in 1 : length(data)) {data[which(is.na(data[,i])),i]<-median(data[,i], na.rm=T)}
      if(dial)  assign(nom, data, envir=.GlobalEnv)
    }
    if(imp== .dico[["txt_multiple_imputation_amelia"]]|| imp=="amelia"){
      amelia(x=data, m = 1, p2s = 0,frontend = FALSE, idvars = id,
             ts = NULL, cs = NULL, polytime = NULL, splinetime = NULL, intercs = FALSE,
             lags = NULL, leads = NULL, startvals = 0, tolerance = 0.0001,
             logs = NULL, sqrts = NULL, lgstc = NULL, noms = noms, ords = ord,
             incheck = TRUE, collect = FALSE, arglist = NULL, empri = NULL,
             priors = NULL, autopri = 0.05, emburn = c(0,0), bounds = NULL,
             max.resample = 100, overimp = which(is.na(data), arr.ind = T), boot.type = "ordinary",
             parallel = c("no", "multicore", "snow"),
             ncpus = getOption("amelia.ncpus", 1L), cl = NULL)->data.am
      data.am$imputations$imp1->data

      if(dial)  assign(nom, data, envir=.GlobalEnv)
    }
    return(data)
  }