% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/ci_plot.R
\name{ci_plot}
\alias{ci_plot}
\title{Confidence interval plot with point estimate}
\usage{
ci_plot(
  ds,
  x = NULL,
  y = NULL,
  vars = NULL,
  dec = 3,
  lbls = NULL,
  title = NULL,
  method = "auto"
)
}
\arguments{
\item{ds}{main input, either data set or logistic model}

\item{x}{text string of main exposure variable}

\item{y}{text string of outcome variable}

\item{vars}{variables for multivariate analysis.}

\item{dec}{Decimals in labels}

\item{lbls}{Labels for variable names}

\item{title}{Plot title. Can be specified later.}

\item{method}{Character vector. The method for the regression.
Can be c("auto", "model").}
}
\value{
ggplot element
}
\description{
Horizontal forest plot of point estimate with confidence intervals.
Includes dichotomous or olr, depending on number of levels in "x".
Title and axis labels can be added to the ggplot afterwards.
}
\examples{
# Auto plot
data(talos)
talos[,"mrs_1"]<-factor(talos[,"mrs_1"],ordered=TRUE)
ci_plot(ds = talos, x = "rtreat", y = "mrs_1", 
vars = c("hypertension","diabetes"))
# Model plot
iris$ord<-factor(sample(1:3,size=nrow(iris),replace=TRUE),ordered=TRUE)
lm <- MASS::polr(ord~., data=iris, Hess=TRUE, method="logistic")
ci_plot(ds = lm, method="model")
}