test.multiplet {hetsurrSurv} | R Documentation |
Tests for heterogeneity across multiple timepoints
Description
Tests for heterogeneity across multiple timepoints
Usage
test.multiplet(t.mult, xone, xzero, deltaone, deltazero, sone, szero, wone,
wzero, w.grd, landmark, extrapolate = TRUE, h.0 = NULL, h.1 = NULL, h.w = NULL,
h.s = NULL, h.w.1 = NULL,type = "cont")
Arguments
t.mult |
Vector of time points |
xone |
x1, observed event time in the treated group |
xzero |
x0, observed event time in the control group |
deltaone |
delta1, event indicator in the treated group |
deltazero |
delta0, event indicator in the control group |
sone |
s1, surrogate marker in the treated group |
szero |
s0, surrogate marker in the control group |
wone |
w1, baseline covariate in the treated group |
wzero |
w0, baseline covariate in the control group |
w.grd |
grid for w where estimation will be provided |
landmark |
t0, landmark time |
extrapolate |
TRUE or FALSE |
h.0 |
bandwidth |
h.1 |
bandwidth |
h.w |
bandwidth |
h.s |
bandwidth |
h.w.1 |
bandwidth |
type |
options are "cont" or "discrete"; type of baseline covariate, default is "cont" |
Value
A list is returned:
pval.multi |
p-value for omnibus test |
pval.con.multi |
p-value for conservative omnibus test (only applicable for continuous W) |
Author(s)
Layla Parast
References
Parast L, Tian L, Cai, T. (2024) "Assessing Heterogeneity in Surrogacy Using Censored Data." Statistics in Medicine, 43(17): 3184-3209.
Examples
data(example.data)
names(example.data)
#computationally intensive
test.multiplet(t.mult = c(1,1.25,1.5), xone=example.data$x1, xzero=example.data$x0,
deltaone=example.data$d1, deltazero=example.data$d0, sone=log(example.data$s1),
szero=log(example.data$s0), wone=log(example.data$w1), wzero=log(example.data$w0),
w.grd=log(seq(0.1,0.9, length=25)), landmark=0.5)