R/t1_normvar.R

In kmcconeghy/Scotty: Scotty: misc. functions

#' @title t1_binvar: "Table One", Binary Variable Summary 
#'
#' @description Function which summarizes dichotomous or binary
#'  variable by a named group
#'
#' @details
#' Supply a dataframe, a variable to summarize, a group variable
#'
#' @param data Dataframe
#' @param .var Variable to be summarized
#' @param .group Group to summarize over
#' @param quietly If FALSE, function will report some internal steps
#' 
#' @return List of length = groups
#'
#' @author Kevin W. McConeghy
#'
#' @examples
#'
#' @export
t1_normvar <- function(data, .var, .group, quietly=T) {
  
  ## Tidy Evaluation
    eq_var <- rlang::enquo(.var)
    nm_var <- paste0(rlang::quo_text(eq_var))
    
    eq_group <- rlang::enquo(.group)
    nm_group <- paste0(rlang::quo_text(eq_group))
  
  ## Sanity Checks
    stopifnot(nm_var %in% names(data))  
    stopifnot(nm_group %in% names(data))  
    stopifnot(class(data[[nm_var]])=="numeric" | class(data[[nm_var]])=="integer")
  
  ## 2 or more
    glevels <- n_distinct(data[[nm_group]])
    if (glevels>3) {warning("4 or more levels to group variable")}
    
  ##Compute values 
    summ <- data %>% 
      group_by(UQ(eq_group)) %>%  
      summarise(mean = mean(rlang::UQ(eq_var), na.rm=T),
                sd = sd(rlang::UQ(eq_var), na.rm=T)) %>%
      arrange(-UQ(eq_group))
    
  ## Compute Scalars
     for (i in 1:glevels) {
       m_nm <- sprintf("%02.1f", summ[[i, "mean"]])
       sd_nm <- sprintf("%02.1f", summ[[i, "sd"]])
       assign(paste0("col_", i), paste0(m_nm, " (", sd_nm, ")"))
     }

  #Build into Row
  result <- t(mget(ls(pattern="col_")))
    
  #Report result
  if (quietly==F) {
    cat("Variable: ", nm_var, " ", 
        "Grouping: ", nm_group, "\n")
    print(paste0(result, sep=", "))
  }
  
  #Return Row
  return(result)
}