I am trying to find a way to make a forest plot of hazard ratios from a Cox-PH model when one of the model variables needs to be stratified. For a non-stratified model, the `ggforest()` function is excellent. Running some example code

```
library(survival)
library(survminer)

model <- coxph(Surv(time, status) ~ sex + rx + adhere,
               data = colon )
ggforest(model)

colon <- within(colon, {
  sex <- factor(sex, labels = c("female", "male"))
  differ <- factor(differ, labels = c("well", "moderate", "poor"))
  extent <- factor(extent, labels = c("submuc.", "muscle", "serosa", "contig."))
})
bigmodel <-
  coxph(Surv(time, status) ~ sex + rx + adhere + differ + extent + node4,
        data = colon )
ggforest(bigmodel)

```

produces this graph

![non-stratified figure](https://i.stack.imgur.com/C9N6M.png)

However if I have to correct for non-proportionality with stratification

```
stratamodel <- coxph(Surv(time, status) ~ sex + strata(rx) + adhere + differ + extent + node4,
                     data = colon )
ggforest(stratamodel)

```

The following error message appears:

> 
> "Error in `[.data.frame`(data, , var) : undefined columns selected
> 
> 
> 

In addition: Warning message:

> 
> In .get\_data(model, data = data) : The `data` argument is not
> provided. Data will be extracted from model fit."
> 
> 
> 

Any suggestions for how to get the information that ggforest needs from the strata model so that it can produce a plot? Thanks for your help!