summary.H2Omodel

The model fit object produced by any stremr S3 function based on h2o

object

Skip all of the h2o-specific model stats, only print the coefficients table (when running <code>fit.algorithm = "glm"</code>).

only.coefs

Format the coefficients into a data.frame table (when running <code>fit.algorithm = "glm"</code>)?

format_table


Prints the modeling summary for the h2o model fit (see <code>h2o</code> R package).


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.

summary.H2Omodel: S3 methods for getting model fit summary for H2Omodel class object

Description

Usage

Arguments

Value