如何从riskRegression：：FGR（）子分布竞争风险模型对象中获取预测和观察到的风险估计？

问：

我想从事件 riskRegression：：FGR（） 竞争风险模型对象中提取观察到的和预测的估计值。

以下是一些模拟数据：

library(simstudy)
library(data.table)
library(survival)
library(riskRegression)
library(cmprsk)
library(prodlim)

#Generate time to event data
d1 <- defData(varname = "x1", formula = .5, dist = "binary")
d1 <- defData(d1, "x2", .5, dist = "binary")
head(dtSurv)
f <- "(time==censor)*0 + (time==event_1)*1 + (time==event_2)*2 + (time==event_3)*3"
cdef <- defDataAdd(varname = "time", 
                   formula = "pmin(censor, event_1, event_2, event_3)", dist = "nonrandom")
cdef <- defDataAdd(varname = "time", 
                   formula = "pmin(censor, event_1, event_2, event_3)", dist = "nonrandom")
cdef <- defDataAdd(cdef, varname = "event", 
                   formula = f, 
                   dist = "nonrandom")
dtSurv_final <- addCompRisk(dtSurv, 
                            events = c("event_1", "event_2", "event_3", "censor"), 
                            timeName = "time", censorName = "censor")
head(dtSurv_final)

#Fit subdistribution model
crr<-riskRegression::FGR(Hist(time, event)~ x1+x2 ,data=dtSurv_final, cause=1)
crr.object<-riskRegression::Score(list(model1=crr),
          Hist(time,event)~1,data=dtSurv_final, cause=1, times=30, plots="cal")
#Store model output 
(cal<-crr.object[["Calibration"]]$plotframe %>% as.data.frame())

我尝试从中提取观察到和预测的风险，但无法这样做。cal