confint.predictCox: Confidence Intervals and Confidence Bands for the predicted... In riskRegression: Risk Regression Models and Prediction Scores for Survival Analysis with Competing Risks

Description

Confidence intervals and confidence Bands for the predicted survival/cumulative Hazard.

Usage

 ``` 1 2 3 4 5 6 7 8 9 10 11``` ```## S3 method for class 'predictCox' confint( object, parm = NULL, level = 0.95, n.sim = 10000, cumhazard.transform = "log", survival.transform = "loglog", seed = NA, ... ) ```

Arguments

 `object` A `predictCox` object, i.e. output of the `predictCox` function. `parm` [character] the type of predicted value for which the confidence intervals should be output. Can be `"survival"` or `"cumhazard"`. `level` [numeric, 0-1] Level of confidence. `n.sim` [integer, >0] the number of simulations used to compute the quantiles for the confidence bands. `cumhazard.transform` [character] the transformation used to improve coverage of the confidence intervals for the cumlative hazard in small samples. Can be `"none"`, `"log"`. `survival.transform` [character] the transformation used to improve coverage of the confidence intervals for the survival in small samples. Can be `"none"`, `"log"`, `"loglog"`, `"cloglog"`. `seed` [integer, >0] seed number set before performing simulations for the confidence bands. If not given or NA no seed is set. `...` not used.

Details

The confidence bands and confidence intervals are automatically restricted to the interval of definition of the statistic, i.e. a confidence interval for the survival of [0.5;1.2] will become [0.5;1].

Brice Ozenne

Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29``` ```library(survival) #### generate data #### set.seed(10) d <- sampleData(40,outcome="survival") #### estimate a stratified Cox model #### fit <- coxph(Surv(time,event)~X1 + strata(X2) + X6, data=d, ties="breslow", x = TRUE, y = TRUE) #### compute individual specific survival probabilities fit.pred <- predictCox(fit, newdata=d[1:3], times=c(3,8), type = "survival", se = TRUE, iid = TRUE, band = TRUE) fit.pred ## check standard error sqrt(rowSums(fit.pred\$survival.iid[,,1]^2)) ## se for individual 1 ## check confidence interval newse <- fit.pred\$survival.se/(-fit.pred\$survival*log(fit.pred\$survival)) cbind(lower = as.double(exp(-exp(log(-log(fit.pred\$survival)) + 1.96 * newse))), upper = as.double(exp(-exp(log(-log(fit.pred\$survival)) - 1.96 * newse))) ) #### compute confidence intervals without transformation confint(fit.pred, survival.transform = "none") cbind(lower = as.double(fit.pred\$survival - 1.96 * fit.pred\$survival.se), upper = as.double(fit.pred\$survival + 1.96 * fit.pred\$survival.se) ) ```

riskRegression documentation built on Jan. 13, 2021, 11:12 a.m.