ahrUser: ahrUser

In mbrueckner/AHR: Estimation and Testing of Average Hazard Ratios

Description

Estimate average hazard ratios from k independent samples based on user-supplied survival function estimator

Usage

ahrUser(L, formula, data, null.theta = NULL, contrast = NULL,
  multi.test = FALSE, cov = FALSE, bootstrap = 0,
  user.survfit = wkm, user.param = list(alpha = 1, var = FALSE, cov =
  FALSE, left.limit = FALSE, rr.subset = rep(TRUE, nrow(data))))

Arguments

L	time-limit specifying time-interval [0,L] over which average hazard ratios will be calculated
formula	an object of class '"formula"' specifying the conditional survival model
data	data frame containing the variables in formula
null.theta	vector specifying the null hypothesis for the average hazard ratios (H_0: theta = null.theta)
contrast	vector of contrasts to test H_0: contrast * (theta - null.theta) = 0
multi.test	calculate multivariate test statistic if TRUE
cov	if TRUE calculate covariance matrix estimator (direct)
bootstrap	if > 0 then use bootstrap to estimate covariance matrix (ignore if cov is TRUE)
user.survfit	user defined function taking vector of times, data.frame and list of parameters returning survival function estimate
user.param	list of parameters passed to function user.survfit

Details

user.survfit must return logV (if user supplied survival function estimator hast independent increments property) or logCOV

Value

An object of class '"ahr"'

References

J.~D. Kalbfleisch and R.~L. Prentice. Estimation of the average hazard ratio. Biometrika, 68(1):105–112, Apr. 1981.

See Also

wkm

Examples

## User supplied survival function estimator (should be exactly the same as
T <- c(rexp(100, 1), rexp(100, 2))
C <- c(rexp(100, 1), rexp(100, 2))
time <- pmin(T, C)
status <- T <= C
trt <- rep(c(0,1), c(100, 100)) # treatment indicator

sfit <- function(times, data, param) {
  fit <- survfit(Surv(Y, D) ~ 1, data=data)
  f <- approxfun(fit$time, fit$surv, method="constant", f=0, yleft=1, rule=2)
  fv <- approxfun(fit$time, fit$std.err^2, method="constant", f=0, yleft=1, rule=2)

  S <- f(times)
  logV <- fv(times) * nrow(data)
  V <- S^2 * logV

  list(times=times, S=S, V=V, logV=logV)
}
fit1 <- ahrUser(2, Surv(time, status) ~ trt,
                data.frame(time=time, status=status, trt=trt), user.survfit=sfit, user.param=list())
fit1
fit2 <- ahrKM(2, Surv(time, status) ~ trt, data.frame(time=time, status=status, trt=trt), cov=FALSE)
fit2

mbrueckner/AHR documentation built on May 22, 2019, 12:57 p.m.