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#' Proportion of Missing Data for Each Case
#'
#' This function computes the proportion of missing data for each case in a matrix
#' or data frame.
#'
#' @param ... a matrix or data frame with incomplete data, where missing
#' values are coded as \code{NA}. Alternatively, an expression
#' indicating the variable names in \code{data} e.g.,
#' \code{na.prop(x1, x2, x3, data = dat)}. Note that the operators
#' \code{.}, \code{+}, \code{-}, \code{~}, \code{:}, \code{::},
#' and \code{!} can also be used to select variables, see 'Details'
#' in the \code{\link{df.subset}} function.
#' @param data a data frame when specifying one or more variables in the
#' argument \code{...}. Note that the argument is \code{NULL}
#' when specifying a matrix or data frame for the argument \code{...}.
#' @param append logical: if \code{TRUE} (default), variable with proportion of
#' missing data is appended to the data frame specified in the
#' argument \code{data}.
#' @param name a character string indicating the name of the variable appended
#' to the data frame specified in the arguement \code{data} when
#' \code{append = TRUE}. By default, the variable is named
#' \code{na.prop}.
#' @param digits an integer value indicating the number of decimal places to be
#' used for displaying proportions.
#' @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} (default), 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.indicator}},
#' \code{\link{na.pattern}}, \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 numeric vector with the same length as the number of rows in \code{x}
#' containing the proportion of missing data.
#'
#' @export
#'
#' @examples
#' # Example 1a: Compute proportion of missing data for each case in the data frame
#' na.prop(airquality)
#'
#' # Example 1b: Alternative specification using the 'data' argument,
#' # append proportions to the data frame 'airquality'
#' na.prop(., data = airquality)
na.prop <- function(..., data = NULL, digits = 2, append = TRUE, name = "na.prop",
as.na = NULL, check = TRUE) {
#_____________________________________________________________________________
#
# Initial Check --------------------------------------------------------------
# Check if input '...' is missing
if (isTRUE(missing(...))) { stop("Please specify the argument '...'.", call. = FALSE) }
# Check if input '...' is NULL
if (isTRUE(is.null(substitute(...)))) { stop("Input specified for the argument '...' is NULL.", call. = FALSE) }
# Check if input 'data' is data frame
if (isTRUE(!is.null(data) && !is.data.frame(data))) { stop("Please specify a data frame for the argument 'data'.", call. = FALSE) }
#_____________________________________________________________________________
#
# Data -----------------------------------------------------------------------
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
## Data using the argument 'data' ####
if (isTRUE(!is.null(data))) {
# Variable names
var.names <- .var.names(..., data = data, check.chr = "a matrix or data frame")
# Extract data
x <- data[, var.names]
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
## Data without using the argument 'data' ####
} else {
# Extract data
x <- eval(..., enclos = parent.frame())
}
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
## Convert user-missing values into NA ####
if (isTRUE(!is.null(as.na))) { x <- .as.na(x, na = as.na) }
#_____________________________________________________________________________
#
# Input Check ----------------------------------------------------------------
# Check input 'check'
if (isTRUE(!is.logical(check))) { stop("Please specify TRUE or FALSE for the argument 'check'.", call. = FALSE) }
if (isTRUE(check)) {
# 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) }
# Check input 'digits'
if (isTRUE(digits %% 1L != 0L | digits < 0L)) { stop("Specify a positive integer value for the argument 'digits'", call. = FALSE) }
# Check input 'append'
if (isTRUE(!is.logical(append))) { stop("Please specify TRUE or FALSE for the argument 'append'.", call. = FALSE) }
}
#_____________________________________________________________________________
#
# Main Function --------------------------------------------------------------
object <- round(rowMeans(is.na(x)), digits = digits)
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
## Append ####
if (isTRUE(!is.null(data) && append)) {
object <- data.frame(data, setNames(as.data.frame(object), nm = name))
}
#_____________________________________________________________________________
#
# Output ---------------------------------------------------------------------
return(object)
}
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