diff --git a/NAMESPACE b/NAMESPACE
index 145233e..4fae426 100644
--- a/NAMESPACE
+++ b/NAMESPACE
@@ -1,6 +1,7 @@
 # Generated by roxygen2: do not edit by hand
 
 export(bpcm)
+export(iptw)
 export(pcbm)
 export(pcbsm)
 export(pcm)
diff --git a/R/iptw.R b/R/iptw.R
new file mode 100644
index 0000000..8ade6ce
--- /dev/null
+++ b/R/iptw.R
@@ -0,0 +1,33 @@
+## File Name: iptw.R
+## File version: 1.0
+
+#' Compute inverse probability of treatement weights (IPTW) for use with PCM
+#'
+#' This function computes IPTW weights for causal inference with the pcm function
+#'
+#' @param df data.frame containing the data
+#' @param Y string containing the name of the column where the dependent variable is stored in df
+#' @param X vector of strings containing the names of the columns where the independent variables are stored in df
+#' @return A vector of IPT weights
+#' @export
+
+iptw <- function(df=NULL,Y=NULL,X=NULL) {
+  if (any(!(Y %in% colnames(df)))) {
+    stop("ERROR: provided Y variable name does not exist in df")
+  }
+  if (!("id"%in%colnames(df))) {
+    stop('ERROR: no column named id provided')
+  }
+  dff <- df[,c(Y,X)]
+  if (length(X)==1) {
+    formu <- paste0(Y,"~",X)
+  } else {
+    formu <- paste0(Y,"~",X[1])
+    for (k in 2:length(X)) {
+      xx <- X[k]
+      formu <- paste0(formu,"+",xx)
+    }
+  }
+  lr_out <- glm(formula = as.formula(formu),data=df,family = binomial(link = 'logit'))
+  psw <- df$TT/fitted(lr_out) + (1-df$TT)/(1-fitted(lr_out))
+}
diff --git a/man/iptw.Rd b/man/iptw.Rd
new file mode 100644
index 0000000..12557f5
--- /dev/null
+++ b/man/iptw.Rd
@@ -0,0 +1,21 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/iptw.R
+\name{iptw}
+\alias{iptw}
+\title{Compute inverse probability of treatement weights (IPTW) for use with PCM}
+\usage{
+iptw(df = NULL, Y = NULL, X = NULL)
+}
+\arguments{
+\item{df}{data.frame containing the data}
+
+\item{Y}{string containing the name of the column where the dependent variable is stored in df}
+
+\item{X}{vector of strings containing the names of the columns where the independent variables are stored in df}
+}
+\value{
+A vector of IPT weights
+}
+\description{
+This function computes IPTW weights for causal inference with the pcm function
+}