hetsurrSurv (version 1.0)

test.multiplet: 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")

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)

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"

Author

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
	# \donttest{
	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)
	# }