survfit method for survstan models

Computes the predicted survivor function for a phpe model.

Usage

# S3 method for class 'survstan'
survfit(formula, newdata = NULL, ...)

Arguments

formula

an object of the class survstan

newdata

a data frame containing the set of explanatory variables; if NULL, a data.frame with the observed failure times and their corresponding estimated baseline survivals is returned.

...

further arguments passed to or from other methods.

Value

a data.frame containing the estimated survival probabilities.

Examples

# \donttest{
library(survstan)
library(ggplot2)
data(ipass)
ipass$arm <- as.factor(ipass$arm)
fit <- ypreg(Surv(time, status)~arm, data=ipass, baseline = "weibull")
summary(fit)
#> Call:
#> ypreg(formula = Surv(time, status) ~ arm, data = ipass, baseline = "weibull")
#> 
#> Yang & Prentice model fit with weibull baseline distribution: 
#> 
#> Regression coefficients:
#>             Estimate Std. Error  z value  Pr(>|z|)    
#> short-arm1  1.361063   0.182368   7.4633  8.44e-14 ***
#> long-arm1  -1.365391   0.082943 -16.4619 < 2.2e-16 ***
#> ---
#> Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
#> 
#> Baseline parameters:
#>       Estimate Std. Error     2.5%  97.5%
#> alpha 1.846062   0.060577 1.731071 1.9687
#> gamma 6.961753   0.166121 6.643658 7.2951
#> --- 
#> loglik = -2772.375   AIC = 5552.751 
newdata <- data.frame(arm=as.factor(0:1))
surv <- survfit(fit, newdata)
ggplot(surv, aes(x=time, y=surv, color = arm)) +
  geom_line()

# }