utils::globalVariables(c("or","ord","lo","up")) #' Forest plot from ordinal logistic regression. #' #' Heavily inspired by https://www.r-bloggers.com/plotting-odds-ratios-aka-a-forrestplot-with-ggplot2/ #' #' @param x input data. #' @param title plot title #' @param dec decimals for labels #' @param lbls labels for variable names. Careful, as the right order is not checked automatically! #' @param hori labels the horizontal axis (this i the y axis as the plot is rotated) #' @param vert labels the horizontal axis (this i the x axis as the plot is rotated) #' @param short flag to half number of ticks on horizontal axis. #' @param input can be either "model", which is a olr model (polr()), or "df", which is a data frame with three columns for OR, lower CI and upper CI. #' #' @return gg object #' @keywords forest plot #' #' @import ggplot2 stats MASS #' #' @export #' #' @examples #' iris$ord<-factor(sample(1:3,size=nrow(iris),replace=TRUE),ordered=TRUE) #' lm <- MASS::polr(ord~., data=iris, Hess=TRUE, method="logistic") #' plot_olr(lm, input="model") plot_olr<-function(x, title = NULL, dec=3, lbls=NULL, hori="OR (95 % CI)", vert="Variables", short=FALSE, input=c("model","df")){ if (input=="model"){ odds <- data.frame(cbind(exp(coef(x)), exp(confint(x)))) } if (input=="df"){ odds <- x } names(odds)<-c("or", "lo", "up") rodds<-round(odds, digits = dec) if (!is.null(lbls)){ odds$vars<-paste0(lbls," \n",paste0(rodds$or," [",rodds$lo,":",rodds$up,"]")) } else { odds$vars<-paste0(row.names(odds)," \n",paste0(rodds$or," [",rodds$lo,":",rodds$up,"]")) } ticks<-c(seq(0, 1, by =.1), seq(1, 10, by =1), seq(10, 100, by =10)) if (short==TRUE){ ticks<-ticks[seq(1, length(ticks), 2)] } odds$ord<-c(nrow(odds):1) odds|> ggplot2::ggplot(mapping = ggplot2::aes(y = or, x = reorder(vars,ord))) + ggplot2::geom_point() + ggplot2::geom_errorbar(mapping = ggplot2::aes(ymin=lo, ymax=up), width=.2) + ggplot2::scale_y_log10(breaks=ticks, labels = ticks) + ggplot2::geom_hline(yintercept = 1, linetype=2) + ggplot2::coord_flip() + ggplot2::labs(title = title, x = vert, y = hori) + ggplot2::theme_bw(14) }