R/tidy_stats.lm.r

In WillemSleegers/tidystats-v0.3: Create a Tidy Statistics Output File

#' Create a tidy stats data frame from an lm object
#'
#' \code{tidy_stats.lm} takes an lm object and converts the object to a tidy
#' stats data frame.
#'
#' @param model Output of \code{lm()}.
#' @param args Unused.
#'
#' @examples
#' # Conduct a regression
#' ctl <- c(4.17,5.58,5.18,6.11,4.50,4.61,5.17,4.53,5.33,5.14)
#' trt <- c(4.81,4.17,4.41,3.59,5.87,3.83,6.03,4.89,4.32,4.69)
#' group <- gl(2, 10, 20, labels = c("Ctl","Trt"))
#' weight <- c(ctl, trt)
#'
#' model_lm <- lm(weight ~ group)
#' tidy_stats(model_lm)
#'
#' @export

tidy_stats.lm <- function(model, args = NULL) {

  # Get summary statistics
  summary <- summary(model)

  # Convert model coefficients output to a data frame
  output_coefficients <- tibble::as_data_frame(summary$coefficients)
  # Not included: Descriptives of residuals, residual standard error, residual
  # degrees of freedom

  # Rename columns
  output_coefficients <- rename_columns(output_coefficients)

  # Set group and term information, and add degrees of freedom
  output_coefficients <- output_coefficients %>%
    dplyr::mutate(
      df = summary$df[2],
      term = names(model$coefficients),
      term_nr = 1:dplyr::n(),
      group = "coefficients") %>%
    tidyr::gather("statistic", "value", -term, -term_nr, -group) %>%
    dplyr::arrange(term_nr)

  # Extract model fit
  output_model <- tibble::data_frame(
    group = "model",
    statistic = c("R squared", "adjusted R squared", "F", "numerator df",
      "denominator df"),
    value = c(summary$r.squared, summary$adj.r.squared, summary$fstatistic[1],
      summary$fstatistic[2], summary$fstatistic[3]))

  # Calculate model fit p value ourselves
  p <- pf(summary$fstatistic[1], summary$fstatistic[2], summary$fstatistic[3],
    lower.tail = FALSE)

  output_model <- dplyr::bind_rows(output_model, data_frame(group = "model",
    statistic = "p", value = p))

  # Combine coefficients and model output
  output <- dplyr::bind_rows(output_coefficients, output_model)

  # Add method
  output <- dplyr::mutate(output, method = "Linear model")

  # Reorder columns
  output <- dplyr::select(output, group, term_nr, term, everything())

  return(output)
}