R/na.indicator.R

In misty: Miscellaneous Functions 'T. Yanagida'

#' Missing Data Indicator Matrix
#'
#' This function creates a missing data indicator matrix \eqn{R} that denotes whether
#' values are observed or missing, i.e., \eqn{r = 1} if a value is observed, and
#' \eqn{r = 0} if a value is missing.
#'
#' @param x           a matrix or data frame.
#' @param as.na       a numeric vector indicating user-defined missing values,
#'                    i.e. these values are converted to \code{NA} before conducting
#'                    the analysis.
#' @param check       logical: if \code{TRUE}, argument specification is checked.
#'
#' @author
#' Takuya Yanagida \email{takuya.yanagida@@univie.ac.at}
#'
#' @seealso
#' \code{\link{as.na}}, \code{\link{na.as}}, \code{\link{na.auxiliary}},
#' \code{\link{na.coverage}}, \code{\link{na.descript}}, \code{\link{na.pattern}},
#' \code{\link{na.prop}}, \code{\link{na.test}}
#'
#' @references
#' Enders, C. K. (2010). \emph{Applied missing data analysis}. Guilford Press.
#'
#' Graham, J. W. (2009). Missing data analysis: Making it work in the real world.
#' \emph{Annual Review of Psychology, 60}, 549-576.
#' https://doi.org/10.1146/annurev.psych.58.110405.085530
#'
#' van Buuren, S. (2018). \emph{Flexible imputation of missing data} (2nd ed.). Chapman & Hall.
#'
#' @return
#' Returns a matrix or data frame with \eqn{r = 1} if a value is observed, and \eqn{r = 0}
#' if a value is missing.
#'
#' @export
#'
#' @examples
#' dat <- data.frame(x = c(1, NA, NA, 6, 3),
#'                   y = c(7, NA, 8, 9, NA),
#'                   z = c(2, NA, 3, NA, 5))
#'
#' # Create missing data indicator matrix \eqn{R}
#' na.indicator(dat)
na.indicator <- function(x, as.na = NULL, check = TRUE) {

  #_____________________________________________________________________________
  #
  # Initial Check --------------------------------------------------------------

  # Check if input 'x' is missing
  if (isTRUE(missing(x))) { stop("Please specify a matrix or data frame for the argument 'x'.", call. = FALSE) }

  # Check if input 'x' is NULL
  if (isTRUE(is.null(x))) { stop("Input specified for the argument 'x' is NULL.", call. = FALSE) }

  # Matrix or data frame for the argument 'x'?
  if (isTRUE(!is.matrix(x) && !is.data.frame(x))) { stop("Please specify a matrix or data frame for the argument 'x'.", call. = FALSE) }

  #_____________________________________________________________________________
  #
  # Data -----------------------------------------------------------------------

  #~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  ## Convert user-missing values into NA ####

  if (isTRUE(!is.null(as.na))) {

    x <- misty::as.na(x, na = as.na, check = check)

  }

  #_____________________________________________________________________________
  #
  # Main Function --------------------------------------------------------------

  object <- apply(x, 2, function(y) as.numeric(!is.na(y)))

  if (isTRUE(is.data.frame(x))) {

    object  <- as.data.frame(object, stringsAsFactors = FALSE)
    row.names(object) <- rownames(x)

  }

  #_____________________________________________________________________________
  #
  # Output ---------------------------------------------------------------------

  return(object)

}