print.GLMmodel

The model fit object produced by functions stremr:::fit.glm or stremr:::fit.speedglm

Additional options passed on to <code>summary.GLMmodel</code>.


Prints the modeling summary for the glm fit (<code>stats::glm.fit</code> or <code>speedglm::speedglm.wfit</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.

print.GLMmodel: S3 methods for printing model fit summary for glmfit class object

Description

Usage

Arguments

Value