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

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

Function to compute the hazard ratio for a risk prediction.

1 2	hazard.ratio(x, surv.time, surv.event, weights, strat, alpha = 0.05, method.test = c("logrank", "likelihood.ratio", "wald"), na.rm = FALSE, ...)

`x`	a vector of risk predictions.
`surv.time`	a vector of event times.
`surv.event`	a vector of event occurrence indicators.
`weights`	weight of each sample.
`strat`	stratification indicator.
`alpha`	apha level to compute confidence interval.
`method.test`	Statistical test to use in order to compute the p-values related to a D. index, see summary.coxph for more details.
`na.rm`	`TRUE` if missing values should be removed.
`...`	additional parameters to be passed to the `coxph` function.

The hazard ratio is computed using the Cox model.

`hazard.ratio`	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 likelihood ratio test whether the hazard ratio is different from 1.
`n`	number of samples used for the estimation.
`coxm`	`coxph.object` fitted on the survival data and `x` (see below).
`data`	list of data used to compute the hazard ratio (`x`, `surv.time` and `surv.event`).

Benjamin Haibe-Kains

Cox, D. R. (1972) "Regression Models and Life Tables", Journal of the Royal Statistical Society Series B, 34, pages 187–220.

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)
hazard.ratio(x=age, surv.time=stime, surv.event=sevent, weights=weight,
  strat=strat)