PTERP: Estimates PTE and RE

In PTERP: PTE and RP for Optimally-Transformed Surrogate

Estimates PTE and RE

Description

Evaluates the strength of a surrogate marker by estimating the proportion of treatment effect explained (PTE) and relative power(RP) for the optimally-transformed version of the surrogate.

Usage

PTERP(data,ncut=c(50,100,150,200,500,1000),n.resam=500)

Arguments

data	data
ncut	relative power is calculated at a specific sample size n; this is a numeric vector of sample sizes for which the user wants the relative power, default is c(50,100,150,200,500,1000)
n.resam	number of times to resample, default is 500

Value

A list of:

ptenew.es	Proportion of treatment effect estimate
rp_i1	Estimate of relative power at n=i1 where i1 is the first value given in ncut
rp_i2	Estimate of relative power at n=i2 where i2 is the second value given in ncut, etc.
pte.se	Standard error estimate for the proportion of treatment effect explained
rp.se.i1	Standard error estimate for the relative power at n=i1 where i1 is the first value given in ncut
rp.se.i2	Standard error estimate for the relative power at n=i2 where i2 is the first value given in ncut, etc.

Author(s)

Xuan Wang

Examples

data(exampledata)

output=PTERP(exampledata,ncut=c(50,100,150,200,500,1000))

#reduce resampling
output=PTERP(exampledata,ncut=c(50,100,150,200,500,1000),n.resam=5)

PTERP documentation built on Oct. 11, 2022, 1:06 a.m.