predict_se {shinyCox}

Creates predicted survival and standard errors for confidence intervals

Description

Adapted from parts of survfit.coxph(), computes predictions for standard errors based on surv_pred_info() output and newdata from the shiny app.

Usage

predict_se(listsurv, coxfit, newdata)

Arguments

listsurv

Output from surv_pred_info() function

coxfit

coxfit object created for predictions. Used to find strata

newdata

Data used to make predicted standard errors

Value

a list of number of subjects for each curve, times at which the curve has a step, number at risk for each time, number of events at each time, number censored at each time (no event but exit risk set), estimated survival, cumulative hazard at each transition, and standard error of the cumulative hazard.

Examples

  library(survival)
  library(shinyCox)
  colondeaths <- colon[colon$etype == 2, ]
  split_colon <- split(colondeaths, colondeaths$rx)

  colon_arm1 <- split_colon$Obs
  colon1ph <- coxph(Surv(time, status) ~
  factor(extent) + nodes + strata(surg) + factor(differ), colon_arm1, x =
  TRUE, model = TRUE)

  new.data = cbind.data.frame(`factor(extent)` = 3, `surg` =
  "surg=0",`factor(differ)` = 2,`nodes` = 5)


  coxfit = prep_coxfit(colon1ph)
  coxlist = surv_pred_info(colon1ph)

  predict_se(coxlist, coxfit, new.data)