Accepts one or more lm objects and returns a single data frame containing the fit statistics R-squared, adjusted R-squared, predictive R-squared and PRESS for each model.

model_fit_stats.R

#' Model Fit Statistics
#' @description Returns lm model fit statistics R-squared, adjusted R-squared,
#'      predicted R-squared and PRESS.
#'      Thanks to John Mount for his 6-June-2014 blog post, R style tip: prefer functions that return data frames" for
#'      the idea \url{http://www.win-vector.com/blog/2014/06/r-style-tip-prefer-functions-that-return-data-frames}
#' @param ... One or more \code{lm()} models.
#' @return A data frame with rows for R-squared, adjusted R-squared, Predictive R-squared and PRESS statistics, and a column for each model passed to the function.
model_fit_stats <- function(...) {
  var_names <- as.character(match.call())[-1]
  dots <- list(...)
  ndots <- length(dots)
  if(all.equal(unlist(lapply(X = dots, FUN = class)), rep("lm", length.out = ndots))){
    return.df <- data.frame(parameter = c("r.squared", "adj.r.squared","pred.r.squared","PRESS"))
    for(i in 1:ndots) {
      r.sqr <- summary(dots[[i]])$r.squared
      adj.r.sqr <- summary(dots[[i]])$adj.r.squared
      pre.r.sqr <- pred_r_squared(dots[[i]])
      PRESS <- PRESS(dots[[i]])
      return.df[paste0(var_names[i])] <- matrix(c(r.sqr, adj.r.sqr, pre.r.sqr, PRESS), nrow = 4, byrow = FALSE)
    }
    #	  r.squared = r.sqr, adj.r.squared = adj.r.sqr, pred.r.squared = pre.r.sqr, press = PRESS)
    return(return.df)
  } else {
    stop("model_fit_stats only works with objects of class 'lm.'")
  }
}