我想计算带有脆弱项的 Cox 比例风险模型的预测幸存者函数 [使用生存包]。似乎当模型中存在脆弱项时，无法计算预测的幸存者函数。

## Example 
require(survival)
data(rats)

## Create fake weight
set.seed(90989)
rats$weight<-runif(nrow(rats),0.2,0.9)

## Cox model with gamma frailty on litter
fit <- coxph(Surv(time, status) ~ rx+weight+frailty(litter,dist="gamma"),
data = rats) 

## Compute survival curve from the cox model for rx=0 and weight=0.5 kg
plot(survfit(fit, newdata=data.frame(rx=0,weight=0.5)),xlab = "time",
ylab="Survival") 

## Running this line, I get following error message:
Error in survfit.coxph(fit, newdata = data.frame(rx = 0, weight = 0.5)) : 
Newdata cannot be used when a model has sparse frailty terms

我尝试通过使用选项同时使用稀疏和非稀疏计算方法 sparse=TRUE, Sparse =FALSE, sparse =0, sparse=5。然而，没有一个工作。

如何根据我的脆弱模型计算预测的幸存者曲线？