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40 lines
1.2 KiB
R
40 lines
1.2 KiB
R
#' Forrest plot from ordinal logistic regression
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#'
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#' Heavily inspired by https://www.r-bloggers.com/plotting-odds-ratios-aka-a-forrestplot-with-ggplot2/
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#' @param x ordinal logistic regression model.
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#' @param title plot title
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#' @param dec decimals for labels
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#' @param lbls labels for variable names. Carefull, as the right order is not checked automatically!
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#' @keywords forestplot
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#' @export
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#' @examples
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#' plot_ord_odds()
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plot_ord_odds<-function(x, title = NULL,dec=3,lbls=NULL){
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require(ggplot2)
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odds<-data.frame(cbind(exp(coef(x)), exp(confint(x))))
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names(odds)<-c("or", "lo", "up")
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rodds<-round(odds,digits = dec)
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if (!is.null(lbls)){
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odds$vars<-paste0(lbls," \n",paste0(rodds$or," [",rodds$lo,":",rodds$up,"]"))
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}
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else {
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odds$vars<-paste0(row.names(odds)," \n",paste0(rodds$or," [",rodds$lo,":",rodds$up,"]"))
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}
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ticks<-c(seq(.1, 1, by =.1), seq(0, 10, by =1), seq(10, 100, by =10))
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odds$ord<-c(nrow(odds):1)
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ggplot(odds, aes(y= or, x = reorder(vars,ord))) +
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geom_point() +
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geom_errorbar(aes(ymin=lo, ymax=up), width=.2) +
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scale_y_log10(breaks=ticks, labels = ticks) +
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geom_hline(yintercept = 1, linetype=2) +
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coord_flip() +
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labs(title = title, x = "Variables", y = "OR (95 % CI)") +
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theme_bw()
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}
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