SurrogateSeq (version 1.1)

delta.e.estimate: Tests for a treatment effect on the primary outcome using surrogate marker information

Description

Nonparametric test for a treatment effect on the primary outcome using surrogate marker information. This test borrows information from a prior study (Study A) about the relationship between the surrogate and the primary outcome to test for a treatment effect in the current study (Study B).

Usage

delta.e.estimate(sone = NULL, szero = NULL, szerop, yzerop, extrapolate = TRUE, 
mat = NULL, n1 = NULL, n0 = NULL)

Value

delta.e

estimated treatment effect using surrogate marker information

sd.closed

estimated standard error of treatment effect estimate

delta.e.z

test statistic

delta.e.p

p-value of test statistic

Arguments

sone

surrogate marker in the treated group in Study B

szero

surrogate marker in the control group in Study B

szerop

surrogate marker in the control group in Study A

yzerop

primary outcome in the control group in Study A

extrapolate

TRUE or FALSE; extrapolate for values outside of the support in Study A

mat

for Study B, the user can either provide sone and szero or can provide a vector, mat, where the first n1 values are the surrogate marker in the treated group in the Study B, and the remaining values are the surrogate marker in the control group in Study B

n1

sample size of treated group in Study B; only needed if mat is provided instead of sone and szero

n0

sample size of control group in Study B; only needed if mat is provided instead of sone and szero

Author

Layla Parast

References

Parast, Cai, and Tian (2023). Using a Surrogate with Heterogeneous Utility to Test for a Treatment Effect. Statistics in Medicine, 42(1): 68-88.

Parast and Bartroff (2024). Group sequential testing of a treatment effect using a surrogate marker. Biometrics, 80(4), ujae108.

Examples

data(example.data)
delta.e.estimate(sone = example.data$s1, szero = example.data$s0, szerop = example.data$s0.p, 
yzerop = example.data$y0.p)

data(StudyA.aids)
data(StudyB.aids)
s1.studyb = StudyB.aids$s1
s0.studyb = StudyB.aids$s0
s0.studya = StudyA.aids$s0

#24 weeks

delta.e.vec = delta.e.estimate(sone=s1.studyb$CD4_24weeks[!is.na(s1.studyb$CD4_24weeks)],
szero=s0.studyb$CD4_24weeks[!is.na(s0.studyb$CD4_24weeks)], szerop = s0.studya$CD4_24weeks, 
yzerop = StudyA.aids$y0, extrapolate = TRUE)
delta.e.vec