gen.wgt {nphPower} | R Documentation |
Weight Function Generation
Description
Generate commonly used weight functions for MaxLRtest
function or pwr2n.NPH
function
Usage
gen.wgt(method = c("LR"), param, theta = 0.5)
Arguments
method |
a vector of text specifying the method(s). The method(s)
must be one or some of c( |
param |
a vector of length 2. If |
theta |
a value within (0,1). If method |
Details
The weight function for Fleming-Harrington (FH) test is S(t)^\rho(1-S(t)^\gamma)
.
If FH
test is specified, both \rho
and \gamma
should be provided.
The weight for Tarone and Ware test is y(t)^{1/2}
, where y(t)
is number
of subjects at risk. The weight for Wilcoxon test is y(t)
. See Klein (2003) for
more details about all those tests. Both Maxcombo test and test proposed by
Cheng and He (2021)
need four weight functions. Cheng's method is more sensitive in detecting
crossing hazards. A nuisance parameter theta
is required to be
specified. Parameter theta
represents the Cumulative Density Function
(CDF) at the crossing time point.
If the hazards crossing
occurs when few events occur yet, a small value should be chosen. The
default value is 0.5.
Function MaxLRtest
supports different base functions including pooled
Kaplan-Meier (K-M) version of CDF functions rather than K-M survival functions.
Therefore, if a F(0,1) test is requested, the returned function is
function(x) {x}
, where x denotes the estimated CDF for
KM
base. All the supported
base functions are increasing over time.
Value
a list of weight function(s).
References
Klein, J. P., & Moeschberger, M. L. (2003). Survival analysis: techniques for censored and truncated data (Vol. 1230). New York: Springer.
Cheng, H., & He, J. (2021). A Maximum Weighted Logrank Test in Detecting Crossing Hazards. arXiv preprint arXiv:2110.03833.
See Also
Examples
#logrank test
gen.wgt(method="LR")
# FH and logrank test
fn <- gen.wgt(method=c("FH","LR"), param = c(1,1))
# maximum weighted logrank test proposed by Cheng, including weight
# for detecting crossing hazards
wcross <- gen.wgt(method="Maxcross", theta = c(0.2))