Description Usage Arguments Details Value References Examples
Find standard error for survival quantile
1 2 | quantileControlTest(timevar1, censor1, timevar2, censor2, q = 0.5, B = 1000,
seed = 1234, plots = FALSE)
|
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 |
Quantile of interest (in terms of CDF). Default is median. |
B |
Number of bootstrap samples. |
seed |
Seed number (for reproducibility). |
plots |
Logical. TRUE to show plot of cumulative distribution functions. |
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.
Returns quantile estimate, bootstrapped standard error, test statistic, and two-sided p-value.
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.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 | #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))
quantileControlTest(t1, c1, t2, c2, q = 0.5, B = 500)
|
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.