diff --git a/DESCRIPTION b/DESCRIPTION
index 38c572d..9b4eddc 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -1,7 +1,7 @@
 Package: daDoctoR
 Type: Package
 Title: FUNCTIONS FOR HEALTH RESEARCH
-Version: 0.1.0.9015
+Version: 0.1.0.9016
 Author@R: c(person("Andreas", "Gammelgaard Damsbo", email = "agdamsbo@pm.me", role = c("cre", "aut")))
 Maintainer: Andreas Gammelgaard Damsbo <agdamsbo@pm.me>
 Description: I am a Danish medical doctor involved in neuropsychiatric research. 
diff --git a/NAMESPACE b/NAMESPACE
index 44eff6c..66d6cd7 100644
--- a/NAMESPACE
+++ b/NAMESPACE
@@ -3,6 +3,7 @@
 export(age_calc)
 export(col_fact)
 export(col_num)
+export(comb_olr)
 export(cpr_check)
 export(cpr_sex)
 export(date_convert)
diff --git a/R/comb_olr.R b/R/comb_olr.R
new file mode 100644
index 0000000..f5b802e
--- /dev/null
+++ b/R/comb_olr.R
@@ -0,0 +1,23 @@
+#' An ordinal logistic regression function for plotting
+#'
+#' Should be combined with "rep_olr()". The confint() function is rather slow, causing the whole function to hang when including many predictors and calculating the ORs with CI.
+#' @param meas primary outcome (factor with >2 levels).
+#' @param vars variables in model. Input as c() of columnnames, use dput().
+#' @param dta data frame to pull variables from.
+#' @keywords olr
+#' @export
+#' @examples
+#' comb_olr()
+
+
+comb_olr<-function(meas,vars,data){
+  require(MASS)
+
+  ad<-vars
+  d<-data
+    d2<-d[,c(meas,ad)]
+    names(d2)[1]<-"meas"
+    x<-polr(meas~.,data = d2,Hess = TRUE)
+    mat<-rbind(mat,c(exp(coef(x)), exp(confint(x))))
+  return(data.frame(mat,stringsAsFactors = FALSE))
+}
diff --git a/R/rep_epi_tests.R b/R/rep_epi_tests.R
index ff17d53..95a50fc 100644
--- a/R/rep_epi_tests.R
+++ b/R/rep_epi_tests.R
@@ -2,8 +2,8 @@
 #'
 #' Repeats the epi.tests from the epiR package. Either gs or test should be of length 1.
 #' @description For bivariate analyses. The confint() function is rather slow, causing the whole function to hang when including many predictors and calculating the ORs with CI.
-#' @param gold the test or meassure used as "golden standard". Format as dichotomised factor.
-#' @param test possible predictive tests to evaluate. Format as dichotomised factor.
+#' @param gold the test or meassure used as "golden standard". Format as list of variable names to include. All variables should be formated as dichotomised factor.
+#' @param test possible predictive tests to evaluate. Format as list of variable names to include. All variables should be formated as dichotomised factor.
 #' @param data dataframe to draw variables from.
 #' @keywords ppv npv sensitivity specificity
 #' @export
diff --git a/man/comb_olr.Rd b/man/comb_olr.Rd
new file mode 100644
index 0000000..cee811a
--- /dev/null
+++ b/man/comb_olr.Rd
@@ -0,0 +1,22 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/comb_olr.R
+\name{comb_olr}
+\alias{comb_olr}
+\title{An ordinal logistic regression function for plotting}
+\usage{
+comb_olr(meas, vars, data)
+}
+\arguments{
+\item{meas}{primary outcome (factor with >2 levels).}
+
+\item{vars}{variables in model. Input as c() of columnnames, use dput().}
+
+\item{dta}{data frame to pull variables from.}
+}
+\description{
+Should be combined with "rep_olr()". The confint() function is rather slow, causing the whole function to hang when including many predictors and calculating the ORs with CI.
+}
+\examples{
+comb_olr()
+}
+\keyword{olr}
diff --git a/man/rep_epi_tests.Rd b/man/rep_epi_tests.Rd
index 68b986c..f93b657 100644
--- a/man/rep_epi_tests.Rd
+++ b/man/rep_epi_tests.Rd
@@ -7,9 +7,9 @@
 rep_epi_tests(gold, test, data)
 }
 \arguments{
-\item{gold}{the test or meassure used as "golden standard". Format as dichotomised factor.}
+\item{gold}{the test or meassure used as "golden standard". Format as list of variable names to include. All variables should be formated as dichotomised factor.}
 
-\item{test}{possible predictive tests to evaluate. Format as dichotomised factor.}
+\item{test}{possible predictive tests to evaluate. Format as list of variable names to include. All variables should be formated as dichotomised factor.}
 
 \item{data}{dataframe to draw variables from.}
 }