pte.survival {OSsurvival}

Estimates the proportion of treatment effect explained

Description

Estimates the proportion of treatment effect explained by the optimally transformed surrogate

Usage

pte.survival(xob, s.ob, deltaob, aob, t, t.0, varind = 0, re = 100)

Arguments

xob

observed survival time

s.ob

surrogate information at time t.0

deltaob

event indicator

aob

treatment indicator

t

time at which the primary outcome is measured

t.0

time at which the surrogate is measured

varind

whether to estimate variance (yes=0, no=1)

re

number of replications for resampling, if varind=0

Value

A list of the following:

pte.est

The estimated proportion of treatment effect explained (PTE) by the optimally transformed surrogate

pte.ese

Standard error estimate for the PTE, provided if var.ind=0

g1.est

Estimated g1

g1.ese

Standard error estimate for ge, provided if var.ind = 0

sgrid

Grid used for the surrogate marker, equally spaced

gs.est

Estimated g(s), optimal transformation of s, for the sgrid

gs.ese

Standard error estimate for g(s), provided if var.ind = 0

Examples

# load the data
data("sysdata")

# time at which the surrogate is measured
t.0 = data.example$t.0

# time at which the primary outcome is measured
t = data.example$t

# observed survival time
xob = data.example$data$xob

# surrogate information at t.0
s.ob = data.example$data$s.ob

# event indicator
deltaob = data.example$data$deltaob

# treatment indicator
aob = data.example$data$aob

# main estimation function
# varind: whether to estimate variance; re:number of replications for resampling
out = pte.survival(xob, s.ob, deltaob, aob, t, t.0, varind=0, re=100)

# estimated PTE
out$pte.est

# estimated g1
out$g1.est

# estimated g2(s) at equally spaced s point
plot(out$sgrid, out$gs.est, type="l", xlab = "Surrogate Marker", ylab = "Optimal Transformation")
#The PTE result indicates that this is a moderate to high surrogate marker in this setting.