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55 lines
1.3 KiB
R
55 lines
1.3 KiB
R
% Generated by roxygen2: do not edit by hand
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% Please edit documentation in R/ci_plot.R
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\name{ci_plot}
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\alias{ci_plot}
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\title{Confidence interval plot with point estimate}
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\usage{
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ci_plot(
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ds,
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x = NULL,
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y = NULL,
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vars = NULL,
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dec = 3,
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lbls = NULL,
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title = NULL,
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method = "auto"
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)
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}
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\arguments{
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\item{ds}{main input, either data set or logistic model}
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\item{x}{text string of main exposure variable}
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\item{y}{text string of outcome variable}
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\item{vars}{variables for multivariate analysis.}
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\item{dec}{Decimals in labels}
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\item{lbls}{Labels for variable names}
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\item{title}{Plot title. Can be specified later.}
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\item{method}{Character vector. The method for the regression.
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Can be c("auto", "model").}
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}
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\value{
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ggplot element
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}
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\description{
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Horizontal forest plot of point estimate with confidence intervals.
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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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\examples{
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# Auto plot
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data(talos)
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talos[,"mrs_1"]<-factor(talos[,"mrs_1"],ordered=TRUE)
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ci_plot(ds = talos, x = "rtreat", y = "mrs_1",
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vars = c("hypertension","diabetes"))
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# Model plot
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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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ci_plot(ds = lm, method="model")
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}
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