hazard.ratio: Function to estimate the hazard ratio through Cox regression
In 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)

Loading required package: survival
Loading required package: prodlim
$hazard.ratio
[1] 0.9976671

$coef
[1] -0.002335581

$se
[1] 0.01424647

$lower
[1] 0.970195

$upper
[1] 1.025917

$p.value
[1] 0.8697696

$n
[1] 100

$coxm
Call:
coxph(formula = Surv(stime, sevent) ~ strata(sstrat) + sx, weights = sweights)

       coef exp(coef) se(coef)     z    p
sx -0.00234   0.99767  0.01425 -0.16 0.87

Likelihood ratio test=0.03  on 1 df, p=0.87
n= 100, number of events= 70 

$data
$data$x
  [1] 55.9 57.1 48.9 45.5 56.1 31.8 56.3 47.2 47.2 40.8 48.8 68.2 53.7 55.2 42.5
 [16] 58.2 41.1 46.7 61.2 53.0 57.8 64.6 43.6 34.5 34.0 68.1 45.2 56.2 56.1 48.4
 [31] 58.1 72.0 70.5 66.3 52.5 54.9 46.8 33.4 67.7 50.3 61.3 26.2 39.4 59.4 58.5
 [46] 64.6 35.9 55.7 55.8 36.9 44.6 69.5 50.5 53.5 43.3 52.8 56.9 58.2 71.5 26.5
 [61] 51.5 36.6 55.5 65.9 44.1 31.7 58.9 65.9 55.2 37.0 50.5 42.2 39.5 73.3 64.0
 [76] 59.4 58.3 41.9 54.8 60.2 56.5 60.4 47.0 74.8 59.7 68.7 56.7 46.9 55.4 58.2
 [91] 40.4 41.4 68.9 46.1 40.2 56.9 44.9 71.6 44.0 43.1

$data$surv.time
  [1] 0.1772 0.0858 0.3273 0.5311 1.4325 1.4688 0.1122 0.3026 0.8770 0.3910
 [11] 1.1858 0.7370 0.2267 0.0698 0.2519 1.6764 1.7902 0.0692 0.4922 1.0174
 [21] 0.5481 0.1440 1.1760 0.0331 0.2638 0.6286 0.5688 0.2527 0.3513 0.2334
 [31] 0.5813 0.6132 0.0117 0.8969 0.8461 0.6515 0.6231 0.0576 0.8562 0.3821
 [41] 0.6177 0.9645 1.5754 0.0204 0.5384 0.0881 1.6552 1.3080 0.7972 1.2041
 [51] 0.6837 0.5931 0.0127 0.0372 0.4109 0.6632 1.7654 0.6298 0.9595 0.9056
 [61] 0.1973 0.4166 0.3069 0.1548 0.3566 0.5638 1.3510 0.5246 0.8472 1.1544
 [71] 0.3653 0.7238 0.2169 0.2382 1.3072 1.1605 0.0110 1.0911 0.5064 0.4733
 [81] 0.3497 1.6239 0.4594 1.0946 0.3565 0.2532 0.5904 0.0307 0.3694 0.2448
 [91] 0.4406 0.1704 0.1505 0.8269 0.5740 1.3492 1.0962 0.8613 0.4346 0.1761

$data$surv.event
  [1] 1 1 1 1 0 0 1 1 1 1 0 1 1 1 1 0 0 1 1 1 0 1 1 1 1 1 1 1 1 1 1 0 1 0 0 1 1
 [38] 1 0 1 0 1 0 1 0 1 0 0 1 0 0 1 1 1 1 1 0 1 0 0 1 1 1 1 1 0 0 0 1 1 1 1 1 1
 [75] 1 0 1 0 0 1 1 0 1 1 1 1 1 1 1 1 1 1 1 0 1 0 0 1 1 1