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data <- mgus2
data$etime <- with(data, ifelse(pstat == 0, futime, ptime))
data$event <- with(data, ifelse(pstat == 0, 2 * death, 1))
data$event <- factor(data$event, 0:2, labels = c("censor", "pcm", "death"))
data$age65 <- with(data, ifelse(age > 65, 1, 0))
data$age65 <- factor(data$age65)
pdata <- survival::finegray(survival::Surv(etime, event) ~ ., data = data)
TableSubgroupMultiCox(formula = Surv(fgstart, fgstop, fgstatus) ~ sex, data = pdata, var_cov = "age", weights = "fgwt", var_subgroups = c("age65"))
#> Variable Count Percent Point Estimate Lower Upper sex=F sex=M P value
#> sex Overall 41775 100 0.77 0.54 1.1 10.4 8.1 0.153
#> 1 age65 <NA> <NA> <NA> <NA> <NA> <NA> <NA> <NA>
#> 2 0 7572 18.1 0.71 0.4 1.27 17.2 10.5 0.252
#> 3 1 34203 81.9 0.8 0.51 1.25 8.7 7.3 0.33
#> P for interaction
#> sex <NA>
#> 1 0.673
#> 2 <NA>
#> 3 <NA>
fgfit <- coxph(Surv(fgstart, fgstop, fgstatus) ~ age + sex,
weight = fgwt, data = pdata, model = T
)
cox2.display(fgfit)
#> $table
#> crude HR(95%CI) crude P value adj. HR(95%CI) adj. P value
#> age "0.98 (0.97,0.99)" "0.003" "0.98 (0.97,0.99)" "0.002"
#> sex: M vs F "0.8 (0.56,1.13)" "0.207" "0.77 (0.54,1.1)" "0.153"
#>
#> $metric
#> [,1] [,2] [,3] [,4]
#> <NA> NA NA NA NA
#> No. of observations "41775" NA NA NA
#> No. of events "115" NA NA NA
#> AIC "1583.87165275874" NA NA NA
#> C-Index "0.548(0.026)" NA NA NA
#>
#> $caption
#> [1] "Cox model on time ('fgstart, fgstop') to event ('fgstatus')"
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.