delta.h.estimate {hettest}

Tests for a treatment effect on the primary outcome using surrogate marker information, accounting for heterogeneity

Description

Nonparametric test for a treatment effect on the primary outcome using surrogate marker information, accounting for heterogeneity in the utility of the surrogate. This test borrows information from a prior study about the relationship between the surrogate and the primary outcome and the baseline covariate to test for a treatment effect in the current study.

Usage

delta.h.estimate(sone = NULL, szero = NULL, wone = NULL, wzero = NULL, szerop, 
wzerop, yzerop, extrapolate = TRUE, mat = NULL, n1 = NULL, n0 = NULL)

Arguments

sone

surrogate marker in the treated group in the current study

szero

surrogate marker in the control group in the current study

wone

baseline covariate in the treated group in the current study

wzero

baseline covariate in the control group in the current study

szerop

surrogate marker in the control group in the prior study

wzerop

baseline covariate in the control group in the prior study

yzerop

primary outcome in the control group in the prior study

extrapolate

TRUE or FALSE; extrapolate for values outside of the support in the prior study

mat

for the current study, the user can either provide sone, szero, wone, wzero or can provide a vector, mat, where the first n1 values are the surrogate marker in the treated group in the current study, the second n0 values are the surrogate marker in the control group in the current study, the next n1 values are the baseline covariate in the treated group in the current study, the next n0 values are the baseline covariate in the control group in the current study

n1

sample size of treated group in the current study; only needed if mat is provided instead of sone, szero, wone, wzero

n0

sample size of control group in the current study; only needed if mat is provided instead of sone, szero, wone, wzero

Value

delta.h

estimated treatment effect using surrogate marker information, account for heterogeneity

sd.h

estimated standard error of treatment effect estimate

test.statistic.h

test statistic for treatment effect

p.value.h

p-value for test statistic

Author(s)

Layla Parast

References

Parast, Cai, and Tian (2022+). Using a Surrogate with Heterogeneous Utility to Test for a Treatment Effect.

Examples

data(example.data)

delta.h.estimate(sone = example.data$s1, szero = example.data$s0, wone = example.data$w1,
 wzero = example.data$w0, szerop = example.data$s0.p, wzerop = example.data$w0.p, 
 yzerop = example.data$y0.p)

#reducing dimension of example data to provide a computationally faster example
delta.h.estimate(sone = example.data$s1[1:100], szero = example.data$s0[1:100], wone =
 example.data$w1[1:100], wzero = example.data$w0[1:100], szerop = 
 example.data$s0.p[1:100], wzerop = example.data$w0.p[1:100], yzerop = 
 example.data$y0.p[1:100])