predictCoxPL: Computation of survival probabilities from Cox regression...

Description Usage Arguments Examples

View source: R/predictCoxPL.R

Description

Same as predictCox except that the survival is estimated using the product limit estimator.

Usage

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predictCoxPL(object, times, newdata = NULL, type = c("cumhazard",
  "survival"), keep.strata = TRUE, keep.infoVar = FALSE, ...)

Arguments

object

The fitted Cox regression model object either obtained with coxph (survival package) or cph (rms package).

times

[numeric vector] Time points at which to return the estimated hazard/cumulative hazard/survival.

newdata

[data.frame or data.table] Contain the values of the predictor variables defining subject specific predictions. Should have the same structure as the data set used to fit the object.

type

[character vector] the type of predicted value. Choices are

  • "hazard" the baseline hazard function when argument newdata is not used and the hazard function when argument newdata is used.

  • "cumhazard" the cumulative baseline hazard function when argument newdata is not used and the cumulative hazard function when argument newdata is used.

  • "survival" the survival baseline hazard function when argument newdata is not used and the cumulative hazard function when argument newdata is used.

Several choices can be combined in a vector of strings that match (no matter the case) strings "hazard","cumhazard", "survival".

keep.strata

[logical] If TRUE add the (newdata) strata to the output. Only if there any.

keep.infoVar

[logical] For internal use.

...

additional arguments to be passed to predictCox.

Examples

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library(survival)

#### generate data ####
set.seed(10)
d <- sampleData(40,outcome="survival")
nd <- sampleData(4,outcome="survival")
d$time <- round(d$time,1)

#### Cox model ####
fit <- coxph(Surv(time,event)~ X1 + X2 + X6,
             data=d, ties="breslow", x = TRUE, y = TRUE)

## exponential approximation
predictCox(fit, newdata = d, times = 1:5)

## product limit
predictCoxPL(fit, newdata = d, times = 1:5)

#### stratified Cox model ####
fitS <- coxph(Surv(time,event)~ X1 + strata(X2) + X6,
             data=d, ties="breslow", x = TRUE, y = TRUE)

## exponential approximation
predictCox(fitS, newdata = d, times = 1:5)

## product limit
predictCoxPL(fitS, newdata = d, times = 1:5)

#### fully stratified Cox model ####
fitS <- coxph(Surv(time,event)~ 1,
             data=d, ties="breslow", x = TRUE, y = TRUE)

## product limit
GS <- survfit(Surv(time,event)~1, data = d)
range(predictCoxPL(fitS)$survival - GS$surv)

fitS <- coxph(Surv(time,event)~ strata(X2),
             data=d, ties="breslow", x = TRUE, y = TRUE)

## product limit
GS <- survfit(Surv(time,event)~X2, data = d)
range(predictCoxPL(fitS)$survival - GS$surv)

riskRegression documentation built on Oct. 5, 2018, 1:03 a.m.