print.summary.parfrailty

Print method for parametric frailty fits

Contains more modern tools for causal inference using regression
standardization. Four general classes of models are implemented; generalized
linear models, conditional generalized estimating equation models,
Cox proportional hazards models, and shared frailty gamma-Weibull models.
Methodological details are described in Sjölander, A. (2016) <doi:10.1007/s10654-016-0157-3>.
Also includes functionality for doubly robust estimation for generalized linear models
in some special cases, and the ability to implement custom models.

Michael Sachs

stdReg2

Regression Standardization for Causal Inference

Michael C Sachs

Arvid Sjölander

Erin E Gabriel

Johan Sebastian Ohlendorff

Adam Brand

print.summary.parfrailty function

<dl><dt>x</dt>
<dd>An object of class "parfrailty"</dd>
<dt>digits</dt>
<dd>Number of digits to print</dd>
<dt>...</dt>
<dd>Not used</dd></dl>

Arguments

Print method for parametric frailty fits — print.summary.parfrailty

<dl>

<dt>x</dt>
<dd>An object of class "parfrailty"</dd>


<dt>digits</dt>
<dd>Number of digits to print</dd>


<dt>...</dt>
<dd>Not used</dd>

</dl>

print.summary.parfrailty: Print method for parametric frailty fits

Description

Usage

Value

Arguments