supControlTest: Supremum-type test for two-sample comparison of survival...

In erickawaguchi/controlTest: Quantile Comparison for Two-Sample Right-Censored Survival Data

Description

Supremum-type test for two-sample comparison of survival quantiles.

Usage

supControlTest(timevar1, censor1, timevar2, censor2, q.min = NULL,
  q.max = 0.5, gridpts = 50, B = 500, seed = 1234, plots = FALSE)

Arguments

timevar1	Vector of observed survival times for sample 1 (control).
censor1	Vector of censoring indicators for sample 1 (1 = uncensored, 0 = censored).
timevar2	Vector of observed survival times for sample 2 (treatment).
censor2	Vector of censoring indicators for sample 2 (1 = uncensored, 0 = censored).
q.min	Smallest quantile (in terms of CDF) to test. Default is the time to earliest event for sample 1.
q.max	Largest quantile (in terms of CDF) to test.
gridpts	Number of grid points between q.min and q.max to test.
B	Number of bootstrap samples.
seed	Seed number (for reproducibility).
plots	Logical. TRUE to show plot of cumulative distribution functions.

Details

It is important to note the possiblilty that the estimated quantile may not be estimable in our bootstrap samples. In such cases the largest observed survival time will be considered as an estimate for the quantile.

Value

Returns quantile estimate, bootstrapped standard error, test statistic, and two-sided p-value.

References

Li, G., Tiwari, R.C., and Wells, M. (1996). "Quantile Comparison Functions in Two-Sample Problems: With Applications to Comparisons of Diagnostic Markers." Journal of the American Statistical Association, 91, 689-698.

Chakraborti, S., and Mukerjee, R. (1989), "A Confidence Interval for a Measure Associated With the Comparison of a Treatment With a Control," South African Statistical Journal, 23, 219-230.

Gastwirth, J. L., and Wang, J. L. (1988), "Control Percentile Test for Censored Data," Journal of Statistical Planning and Inference, 18, 267-276.

Examples

#Reference: Survival Analysis Techniques for Censored and Truncated Data.
#Klein and Moeschberger (1997) Springer.
#Data: Chapter 7.6 Example 7.9 (p. 211)
library(controlTest)
t1 <- c(1, 63, 105, 129, 182, 216, 250, 262, 301, 301,
       342, 354, 356, 358, 380, 383, 383, 338, 394, 408, 460, 489,
       499, 523, 524, 535, 562, 569, 675, 676, 748, 778, 786, 797,
       955, 968, 1000, 1245, 1271, 1420, 1551, 1694, 2363, 2754, 2950)
t2 <- c(17, 42, 44, 48, 60, 72, 74, 95, 103, 108, 122, 144, 167, 170,
       183, 185, 193, 195, 197, 208, 234, 235, 254, 307, 315, 401, 445,
       464, 484, 528, 542, 547, 577, 580, 795, 855, 1366, 1577, 2060,
       2412, 2486, 2796, 2802, 2934, 2988)
c1 <- c(rep(1, 43), 0, 0)
c2 <- c(rep(1, 39), rep(0, 6))
supControlTest(t1, c1, t2, c2, q.max = 0.5, B = 500)

erickawaguchi/controlTest documentation built on May 17, 2019, 5:50 p.m.