d_example_multiple: Hypothetical survival data with multiple surrogate markers

In laylaparast/Rsurrogate: Robust Estimation of the Proportion of Treatment Effect Explained by Surrogate Marker Information

Hypothetical survival data with multiple surrogate markers

Description

Hypothetical survival data with multiple surrogate markers to be used in examples.

Usage

data(d_example_multiple)

Format

A list with 6 elements representing 1000 observations from a control group and 1000 observations from a treatment group:

s1

Surrogate marker measurements for treated observations; these markers are measured at time = 0.5. For observations that experience the primary outcome or are censored before 0.5, the surrogate values are NA.

x1

The observed event or censoring time for treated observations; X = min(T, C) where T is the time of the primary outcome and C is the censoring time.

delta1

The indicator identifying whether the treated observation was observed to have the event or was censored; D =1*(T<C) where T is the time of the primary outcome and C is the censoring time.

s0

Surrogate marker measurements for control observations; these markers are measured at time = 0.5. For observations that experience the primary outcome or are censored before 0.5, the surrogate values are NA.

x0

The observed event or censoring time for control observations; X = min(T, C) where T is the time of the primary outcome and C is the censoring time.

delta0

The indicator identifying whether the control observation was observed to have the event or was censored; D =1*(T<C) where T is the time of the primary outcome and C is the censoring time.

Examples

data(d_example_multiple)
names(d_example_multiple)

laylaparast/Rsurrogate documentation built on Sept. 28, 2022, 12:25 p.m.