OdatDT_10K


Simulated dataset containing 10,000 i.i.d. observations organized in long format as person-time rows.
The binary exposure is <code>TI</code> and binary outcome is <code>Y.tplus1</code>. See /tests/
for R code that generated this data as well as R code that uses stremr to analyze this data.


datasets

Analysis of longitudinal time-to-event or time-to-failure data.
Estimates the counterfactual discrete survival curve under static, dynamic and
stochastic interventions on treatment (exposure) and monitoring events over time.
Estimators (IPW, MSM-IPW, GCOMP, longitudinal TMLE) adjust for measured time-varying
confounding and informative right-censoring. Model fitting can be performed either
with GLM or H2O-3 machine learning libraries.
The exposure, monitoring and censoring variables can be coded as either binary,
categorical or continuous. Each can be multivariate (e.g., can use more than one
column of dummy indicators for different censoring events).
The input data needs to be in long format.

Oleg Sofrygin

stremr

Streamlined Estimation of Survival for Static, Dynamic and
Stochastic Treatment and Monitoring Regimes

OdatDT_10K function

A data frame with 10,000 observations and variables:
<dl> </dl>

OdatDT_10K: An example of a dataset in long format with random monitoring process and no right censoring.

Description

Usage

Arguments

Format