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

 confint.predictCox R Documentation

## Confidence Intervals and Confidence Bands for the predicted Survival/Cumulative Hazard

### Description

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

### Usage

```## 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

```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 March 23, 2022, 5:07 p.m.