2022-09-22 19:53:15 +02:00
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% Generated by roxygen2: do not edit by hand
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% Please edit documentation in R/plot_olr.R
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2022-09-23 12:05:32 +02:00
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\name{plot_olr}
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\alias{plot_olr}
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2022-09-22 19:53:15 +02:00
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\title{Forrest plot from ordinal logistic regression.}
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\usage{
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plot_olr(
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2022-09-22 19:53:15 +02:00
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x,
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title = NULL,
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dec = 3,
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lbls = NULL,
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hori = "OR (95 \% CI)",
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vert = "Variables",
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short = FALSE,
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input = c("model", "df")
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)
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}
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\arguments{
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\item{x}{input data.}
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\item{title}{plot title}
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\item{dec}{decimals for labels}
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\item{lbls}{labels for variable names. Carefull, as the right order is not checked automatically!}
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\item{hori}{labels the horizontal axis (this i the y axis as the plot is rotated)}
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\item{vert}{labels the horizontal axis (this i the x axis as the plot is rotated)}
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\item{short}{flag to half number of ticks on horizontal axis.}
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\item{input}{can be either "model", which is a olr model (polr()), or "df", which is a dataframe whith three columns for OR, lower CI and upper CI.}
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}
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\value{
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gg object
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}
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\description{
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Heavily inspired by https://www.r-bloggers.com/plotting-odds-ratios-aka-a-forrestplot-with-ggplot2/
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}
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\examples{
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iris$ord<-factor(sample(1:3,size=nrow(iris),replace=TRUE),ordered=TRUE)
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lm <- MASS::polr(ord~., data=iris, Hess=TRUE, method="logistic")
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plot_olr(lm, input="model")
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}
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2022-09-23 09:14:47 +02:00
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\keyword{forest}
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\keyword{plot}
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