2022-10-11 08:25:39 +02:00
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utils::globalVariables(c("vname"))
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#' Confidence interval plot with point estimate
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#'
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#' Horizontal forest plot of point estimate with confidence intervals. Includes dichotomous or olr, depending on number of levels in "x".
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#' Title and axis labels can be added to the ggplot afterwards.
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#'
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#' @param ds data set
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#' @param x text string of main exposure variable
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#' @param y text string of outcome variable
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#' @param vars variables for multivariate analysis.
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#' @param dec Decimals in labels
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#' @param lbls Labels for variable names
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#' @param title Plot title. Can be specified later.
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#'
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#' @return ggplot element
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#' @export
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#'
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#' @import ggplot2
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#' @importFrom MASS polr
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2022-12-21 07:30:06 +01:00
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#' @importFrom stats as.formula coef confint formula lm quantile reorder
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2022-10-11 08:25:39 +02:00
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#'
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#' @examples
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#' data(talos)
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#' talos[,"mrs_1"]<-factor(talos[,"mrs_1"],ordered=TRUE)
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#' talos$bin <- factor(sample(1:2, size = nrow(talos), replace = TRUE))
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#' ci_plot(ds = talos, x = "rtreat", y = "mrs_1", vars = c("hypertension","diabetes"))
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ci_plot<- function(ds, x, y, vars, dec=3, lbls=NULL, title=NULL){
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if (is.factor(ds[y])) stop("Outcome has to be factor")
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if (length(levels(ds[,y])) > 2){
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m <- MASS::polr(as.formula(paste0(y,"~",x,"+.")), data=ds[,unique(c(x, y, vars))], Hess=TRUE, method="logistic")
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if (is.null(title)) title <- "Ordinal logistic regression"
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}
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if (length(levels(ds[,y])) == 2){
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m <- lm(as.formula(paste0(y,"~",x,"+.")), data=ds[,unique(c(x, y, vars))])
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if (is.null(title)) title <- "Binary logistic regression"
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}
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odds <- data.frame(cbind(exp(coef(m)), exp(confint(m))))
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names(odds)<-c("or", "lo", "up")
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rodds<-round(odds, digits = dec)
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if (is.null(lbls)){
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odds$vname<-paste0(row.names(odds)," \n",paste0(rodds$or," [",rodds$lo,":",rodds$up,"]"))
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} else {
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odds$vname<-paste0(lbls," \n",paste0(rodds$or," [",rodds$lo,":",rodds$up,"]"))
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}
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odds$ord<-c(nrow(odds):1)
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ggplot2::ggplot(data = odds, mapping = ggplot2::aes(y = or, x = reorder(vname,ord))) +
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ggplot2::geom_point() +
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ggplot2::geom_errorbar(mapping = ggplot2::aes(ymin=lo, ymax=up), width = 0.2) +
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ggplot2::scale_y_log10() +
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ggplot2::geom_hline(yintercept = 1, linetype=2) +
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ggplot2::labs(title=title) +
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ggplot2::coord_flip()
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}
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