#' Tells which variable to eliminate to get more observations.
#'
#' This function helps you to decide which variable is restricting your analysis
#' by having the highest number of missing values in the selected set.
#'
#' @param predictors Predictors are the known variables, based on which
#' we want to conduct our predicting.
#' @param outcome is the character string specifying the outcome variable.
#' This variable has to be a part of the database (db)
#' @param db The database on which we should perform the operations
#'
#' @return The table of non-missing observations after eliminating the variable
#' to the left.
#'
#' @export
#'
#' @examples
#' which.restricts(c("d_age","b_sex"),"ANAscore",data)
#### Funkcja która mówi ile zyskam obserwacji jak ją zastosuję
which.restricts <- function(predictors,outcome,db){
len <- length(predictors)
obs <- rep(0,len)
name <- rep(0,len)
for (i in 1:len){
obs[i] <- length(na.omit(db[c(outcome,predictors[-i])])[,1])
name[i] <- predictors[i]
}
print(cbind(name,obs))
}
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