R/furniture.R

In furniture: Furniture for Quantitative Scientists

#' furniture
#' 
#' The furniture package offers simple functions (i.e. pieces of furniture) and an 
#' operator that are aimed at helping applied researchers explore and communicate 
#' their data as well as clean their data in a tidy way. The package follows similar 
#' semantics to the "tidyverse" packages. It contains several table functions (\code{table1()})
#' being the core one.
#' 
#' \itemize{
#'   \item \code{table1} provides a well-formatted descriptive table often seen 
#'         as table 1 in academic journals (also a version that simplifies the output is 
#'         available as \code{simple_table1}),
#'   \item \code{washer} provides a simple way to clean up data where there are placeholder
#'         values, and
#'   \item \code{\%xt\%} is an operator that takes two factor variables and creates a cross tabulation and
#'         tests for significance via a chi-square test.
#' }
#' 
#' Table 1 is the main function in furniture. It is useful in both data exploration 
#' and data communication. With minimal cleaning, the outputted table can be put into 
#' an academic, peer reviewed journal manuscript. As such, it is very useful in exploring
#' your data when you have a stratifying variable. For example, if you are exploring whether
#' the means of several demographic and behavioral characteristics are related to a health condition,
#' the health condition (i.e. "yes" or "no"; "low", "mid", or "high"; or a list of conditions) as
#' the stratifying variable. With little code, you can test for associations and check means or 
#' counts by the stratifying variable. See the vignette for more information. 
#' 
#' Note: furniture is meant to make life more comfortable and beautiful. In like manner, this package
#' is designed to be "furniture" for quantitative research.
#' 
#' @examples
#' \dontrun{
#' 
#' library(furniture)
#' 
#' ## Table 1
#' data %>%
#'   table1(var1, var2, var3, 
#'          splitby = ~groupvar,
#'          test = TRUE)
#' 
#' ## Table F
#' data %>%
#'   tableF(var1)
#' 
#' ## Washer
#' x = washer(x, 7, 8, 9)
#' x = washer(x, is.na, value=0)
#' 
#' }
#' 
#' @docType package
#' @name furniture
#' @aliases furniture-package
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