diff --git a/R/ppdpps.R b/R/ppdpps.R
index 5d9d4e8..93b5319 100644
--- a/R/ppdpps.R
+++ b/R/ppdpps.R
@@ -181,9 +181,9 @@ calc_surv_psmpps <- function(totime, fromtime=0, ptdata, dpam, psmtype="simple")
 #' @importFrom rlang .data
 #' @return `adj` is the hazard adjusted for constraints, `unadj` is the unadjusted hazard
 #' @noRd
-pickout_psmhaz <- function(timevar, endpoint=NA, dpam, psmtype) {
+pickout_psmhaz <- function(timevar, endpoint=NA, ptdata, dpam, psmtype) {
   # Run calculation of all hazards
-  allhaz <- calc_haz_psm(timevar, dpam, psmtype)
+  allhaz <- calc_haz_psm(timevar, ptdata, dpam, psmtype)
   # Required hazard, unadjusted
   h_unadj <- dplyr::case_when(
     endpoint=="TTP" ~ allhaz$unadj$ttp,
@@ -242,14 +242,14 @@ pickout_psmhaz <- function(timevar, endpoint=NA, dpam, psmtype) {
 #' #   dpam=params,
 #' #   psmtype="simple")
 #' # psmh_simple$graph
-graph_psm_hazards <- function(timevar, endpoint, dpam, psmtype) {
+graph_psm_hazards <- function(timevar, endpoint, ptdata, dpam, psmtype) {
   # Declare local variables
   Adjusted <- Unadjusted <- Time <- Hazard <- Method <- NULL
   # Convert endpoint to upper case text
   endpoint <- toupper(endpoint)
   # Pull out hazards to plot (inefficiently calls function twice, but is quite quick)
-  adjhaz <- timevar |> purrr::map_vec(~pickout_psmhaz(.x, endpoint, dpam, psmtype)$adj)
-  unadjhaz <- timevar |> purrr::map_vec(~pickout_psmhaz(.x, endpoint, dpam, psmtype)$unadj)
+  adjhaz <- timevar |> purrr::map_vec(~pickout_psmhaz(.x, endpoint, ptdata, dpam, psmtype)$adj)
+  unadjhaz <- timevar |> purrr::map_vec(~pickout_psmhaz(.x, endpoint, ptdata, dpam, psmtype)$unadj)
   # Create dataset for graphic
   result_data <- dplyr::tibble(Time=timevar, Adjusted=adjhaz, Unadjusted=unadjhaz) |>
       tidyr::pivot_longer(cols=c(Adjusted, Unadjusted),
@@ -284,23 +284,24 @@ graph_psm_hazards <- function(timevar, endpoint, dpam, psmtype) {
 #' psms_simple <- graph_psm_survs(
 #'   timevar=6*(0:10),
 #'   endpoint="OS",
+#'   ptdata=bosonc,
 #'   dpam=params,
 #'   psmtype="simple"
 #' )
 #' psms_simple$graph
 #' }
-graph_psm_survs <- function(timevar, endpoint, dpam, psmtype) {
+graph_psm_survs <- function(timevar, endpoint, ptdata, dpam, psmtype) {
   # Declare local variables
   Adjusted <- Unadjusted <- Time <- Survival <- Method <- NULL
   # Convert endpoint to upper case text
   endpoint <- toupper(endpoint)
   # Unadjusted hazard
   haz_unadj <- function(time) {
-    pickout_psmhaz(time, endpoint, dpam, psmtype)$unadj
+    pickout_psmhaz(time, endpoint, ptdata, dpam, psmtype)$unadj
   }
   # Adjusted hazard
   haz_adj <- function(time) {
-    pickout_psmhaz(time, endpoint, dpam, psmtype)$adj
+    pickout_psmhaz(time, endpoint, ptdata, dpam, psmtype)$adj
   }
   # Unadjusted cumulative hazard
   cumhaz_unadj <- function(time) {
diff --git a/man/graph_psm_hazards.Rd b/man/graph_psm_hazards.Rd
index 62ef939..e8fb076 100644
--- a/man/graph_psm_hazards.Rd
+++ b/man/graph_psm_hazards.Rd
@@ -60,7 +60,6 @@ params <- list(
 # psmh_simple <- graph_psm_hazards(
 #   timerange=(0:10)*6,
 #   endpoint="OS",
-#   ptdata=bosonc,
 #   dpam=params,
 #   psmtype="simple")
 # psmh_simple$graph
diff --git a/man/graph_psm_survs.Rd b/man/graph_psm_survs.Rd
index 88ce302..9427489 100644
--- a/man/graph_psm_survs.Rd
+++ b/man/graph_psm_survs.Rd
@@ -4,13 +4,24 @@
 \alias{graph_psm_survs}
 \title{Graph the PSM survival functions}
 \usage{
-graph_psm_survs(timevar, endpoint, dpam, psmtype)
+graph_psm_survs(timevar, endpoint, ptdata, dpam, psmtype)
 }
 \arguments{
 \item{timevar}{Vector of times at which to calculate the hazards}
 
 \item{endpoint}{Endpoint for which hazard is required (TTP, PPD, PFS, OS or PPS)}
 
+\item{ptdata}{Dataset of patient level data. Must be a tibble with columns named:
+\itemize{
+\item \code{ptid}: patient identifier
+\item \code{pfs.durn}: duration of PFS from baseline
+\item \code{pfs.flag}: event flag for PFS (=1 if progression or death occurred, 0 for censoring)
+\item \code{os.durn}: duration of OS from baseline
+\item \code{os.flag}: event flag for OS (=1 if death occurred, 0 for censoring)
+\item \code{ttp.durn}: duration of TTP from baseline (usually should be equal to pfs.durn)
+\item \code{ttp.flag}: event flag for TTP (=1 if progression occurred, 0 for censoring).
+}}
+
 \item{dpam}{List of survival regressions for each endpoint:
 \itemize{
 \item pre-progression death (PPD)
@@ -46,12 +57,9 @@ params <- list(
   pps_cf = find_bestfit_par(fits$pps_cf, "aic")$fit,
   pps_cr = find_bestfit_par(fits$pps_cr, "aic")$fit
 )
-# Original OS graphic
-graph_orig <- graph_survs(ptdata=bosonc, dpam=params)
-graph_orig$graph$os
-# New graphic illustrating effect of constraints on OS model
+# Graphic illustrating effect of constraints on OS model
 psms_simple <- graph_psm_survs(
-  timerange=6*(0:10),
+  timevar=6*(0:10),
   endpoint="OS",
   ptdata=bosonc,
   dpam=params,
diff --git a/vignettes/mortality-adjustments.Rmd b/vignettes/mortality-adjustments.Rmd
index e005885..b26e565 100644
--- a/vignettes/mortality-adjustments.Rmd
+++ b/vignettes/mortality-adjustments.Rmd
@@ -114,7 +114,6 @@ First we load the packages we need - all of which are suggested for or imported
 
 ```{r packages, message=FALSE}
 library("dplyr")
-library("HMDHFDplus")
 library("psm3mkv")
 library("tibble")
 ```
@@ -124,6 +123,9 @@ library("tibble")
 In order to apply constraints to background mortality, we need some background mortality data, in the form of a lifetable. We can take this from the Human Mortality Database using the *HMDHFDplus* package mentioned above (with thanks to Robert Hettle for the recommendation). The lifetable will need to start from an assumed age at baseline. Lifetables are constructed by time in years.
 
 ```{r ltable1, eval=FALSE}
+# HMD HFD package
+library("HMDHFDplus")
+
 # Assumed population age at baseline (time=0)
 baseage <- 51.0