mfi score calc

R/mfi_calc.R

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+#' Title
+#'
+#' @param d data frame or tibble
+#' @param var numeric vector of indices of columns to reverse
+#'
+#' @return data.frame or tibble depending on input
+#'
+#' @examples
+#' # rep_len(sample(1:5),length.out = 100) |> matrix(ncol=10) |> multi_rev(2:4)
+multi_rev <- function(d, var){
+  # Forcing and coercing to numeric
+  dm <- d |> as.matrix() |> 
+    as.numeric()|> 
+    matrix(ncol=ncol(d)) |> 
+    data.frame()
+  
+  # Reversing everything (fast enough not to subset)
+  dr <- range(dm,na.rm=TRUE) |> sum()-dm
+  
+  # Inserting reversed scores in correct places
+  for (i in var){
+    dm[i] <- dr[i]
+  }
+  
+  if (tibble::is_tibble(d)){
+    tibble::tibble(dm)
+  } else {
+      dm
+    }
+
+}
+
+#' MFI domain score calculator
+#'
+#' @param ds data set of MFI scores, 20 columns
+#' @param reverse.vars variables/columns to reverse
+#' @param reverse reverse scoring
+#'
+#' @return tibble of domain scores
+#' @export
+#'
+#' @examples
+#' mfi_mess <- data.frame(matrix(
+#' sample(c(" 1. ", "2. -A", "3.", " 4  ", "5.", NA),200,replace=TRUE),ncol=20))
+#' mfi_mess |> mfi_domains()
+mfi_domains <-
+  function(ds,
+           reverse = TRUE,
+           reverse.vars = c(2, 5, 9, 10, 13, 14, 16, 17, 18, 19)) {
+    
+  if(ncol(ds)!=20){
+    stop("The supplied dataset should only contain the 20 MFI subscores")}
+  
+  # Subscore indexes
+  indexes <- list(
+    data.frame(grp="gen", ndx=c(1, 5, 12, 16)),
+    data.frame(grp="phy", ndx=c(2, 8, 14, 20)),
+    data.frame(grp="act", ndx=c(3, 6, 10, 17)),
+    data.frame(grp="mot", ndx=c(4, 9, 15, 18)),
+    data.frame(grp="men", ndx=c(7, 11, 13, 19))
+  ) |> dplyr::bind_rows() |> dplyr::arrange(ndx)
+  
+  # Removes padding and converts to numeric
+  ds_n <- ds |> dplyr::mutate_if(is.factor, as.character) |> 
+    dplyr::mutate(dplyr::across(tidyselect::everything(),
+                  # Removes everything but the leading alphanumeric character
+                  # Data should be cleaned accordingly
+                  ~str_extract(d=.,pattern="[[:alnum:]]")))
+  
+  # Assumes reverse scores are not correctly reversed
+  if (reverse){ds_n <- ds_n |> multi_rev(var=reverse.vars)}
+  
+  # Domain wise summations
+  split.default(ds_n, factor(indexes$grp)) |> 
+    lapply(function(x){
+      apply(x, MARGIN = 1, sum, na.ignore=FALSE)
+    }) |> dplyr::bind_cols()
+  
+  }

man/mfi_domains.Rd

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+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/mfi_calc.R
+\name{mfi_domains}
+\alias{mfi_domains}
+\title{MFI domain score calculator}
+\usage{
+mfi_domains(
+  ds,
+  reverse = TRUE,
+  reverse.vars = c(2, 5, 9, 10, 13, 14, 16, 17, 18, 19)
+)
+}
+\arguments{
+\item{ds}{data set of MFI scores, 20 columns}
+
+\item{reverse}{reverse scoring}
+
+\item{reverse.vars}{variables/columns to reverse}
+}
+\value{
+tibble of domain scores
+}
+\description{
+MFI domain score calculator
+}
+\examples{
+mfi_mess <- data.frame(matrix(
+sample(c(" 1. ", "2. -A", "3.", " 4  ", "5.", NA),200,replace=TRUE),ncol=20))
+mfi_mess |> mfi_domains()
+}

man/multi_rev.Rd

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+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/mfi_calc.R
+\name{multi_rev}
+\alias{multi_rev}
+\title{Title}
+\usage{
+multi_rev(d, var)
+}
+\arguments{
+\item{d}{data frame or tibble}
+
+\item{var}{numeric vector of indices of columns to reverse}
+}
+\value{
+data.frame or tibble depending on input
+}
+\description{
+Title
+}
+\examples{
+# rep_len(sample(1:5),length.out = 100) |> matrix(ncol=10) |> multi_rev(2:4)
+}