balanced.hazard.ratio: Function to estimate the balanced hazard ratio through Cox...
In survcomp: Performance Assessment and Comparison for Survival Analysis

Description Usage Arguments Details Value Author(s) References See Also Examples

Function to compute the balanced hazard ratio for a risk group prediction.

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balanced.hazard.ratio(x, surv.time, surv.event, alpha = 0.05,
method.test = c("logrank", "likelihood.ratio", "wald"),
ties = c("efron", "breslow", "exact"), weights, strat, ...)

`x`	a vector of risk group predictions.
`surv.time`	a vector of event times.
`surv.event`	a vector of event occurrence indicators.
`alpha`	alpha level to compute confidence interval.
`method.test`	...
`ties`	...
`weights`	...
`strat`	...
`...`	additional parameters to be passed to the `hazard.ratio` and the `coxph` functions.

The balanced hazard ratio is computed using the Cox model.

`balanced.hazard.ratio`	balanced hazard ratio estimate.
`coef`	coefficient (beta) estimated in the cox regression model.
`se`	standard error of the coefficient (beta) estimate.
`lower`	lower bound for the confidence interval.
`upper`	upper bound for the confidence interval.
`p.value`	p-value computed using the score (logrank) test whether the balanced hazard ratio is different from 1.
`n`	number of samples used for the estimation.
`coxm`	`coxph.object` fitted on the survival data and `x`.
`data`	list of data used to compute the balanced hazard ratio (`x`, `surv.time` and `surv.event`).

Samuel Branders

Branders, S. and Dupont, P. (2015) "A balanced hazard ratio for risk group evaluation from survival data", Statistics in Medicine, 34(17), pages 2528–2543.

hazard.ratio, coxph, coxph.object

set.seed(12345)
age <- rnorm(100, 50, 10)
stime <- rexp(100)
cens   <- runif(100,.5,2)
sevent  <- as.numeric(stime <= cens)
stime <- pmin(stime, cens)
strat <- sample(1:3, 100, replace=TRUE)
weight <- runif(100, min=0, max=1)
balanced.hazard.ratio(x=age, surv.time=stime, surv.event=sevent, weights=weight,
  strat=strat)