Longitudinal Mediators with Survival Outcome Dataset for HIMA Demo
Source:R/hima_data.R
SurvivalLongData.RdA simulated dataset for demonstrating high-dimensional and longitudinal mediation analysis with survival outcomes in a counting-process framework. The data were generated under a longitudinal mediator model and a piecewise-constant Weibull survival model, mimicking real-world analysis settings.
Format
A list with the following components:
- PhenoData
A data frame where each row represents one interval (
tstart,tstop) for a subject in counting-process format. It contains:- ID
Subject identifier (may appear multiple times due to interval splitting).
- Tstart
Start time of the interval.
- Tstop
Stop time of the interval (event or censoring time).
- Status
Event indicator for the interval (
1 = event,0 = no event).- Treatment
Exposure variable for each subject.
- Sex
Binary covariate:
1 = male,0 = female.- Age
Age of the subject in years.
- Mediator
A numeric matrix of high-dimensional longitudinal mediators aligned with the rows of
PhenoData. Columns correspond to mediator variables (M1,M2, …), and rows correspond to observation intervals in the counting-process setup.
Examples
data(SurvivalLongData)
head(SurvivalLongData$PhenoData)
#> ID Tstart Tstop Status Treatment Sex Age
#> 1 1 0.0 0.2000000 0 0.7204068 0 38
#> 2 1 0.2 0.8242078 1 0.7204068 0 38
#> 3 2 0.0 0.2000000 0 0.5899158 1 22
#> 4 2 0.2 0.6869848 1 0.5899158 1 22
#> 5 3 0.0 0.2000000 0 0.2415349 1 47
#> 6 3 0.2 0.7643494 1 0.2415349 1 47