get_FUPtimes

Either a list of data.table containing weights (one for each separate regimen/intervention) or a single data.table with
weights for one regimen / intervention.

wts_data

Name of the column containing subject-specific identifier in the input data.

IDnode

Name of the column containing the time/period variable in the input data.

tnode


Subject specific follow-up times for each regimen in <code>wts_data</code>.


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.

get_FUPtimes: Follow-up times by regimen

Description

Usage

Arguments

Value

See Also