summary.pseudoglm

A user friendly, easy to understand way of doing event
history regression for marginal estimands of interest,
including the cumulative incidence and the restricted mean
survival, using the pseudo observation framework for
estimation. For a review of the methodology, see Andersen and
Pohar Perme (2010) <doi:10.1177/0962280209105020> or Sachs
and Gabriel (2022) <doi:10.18637/jss.v102.i09>. The
interface uses the well known formulation of a generalized
linear model and allows for features including plotting of
residuals, the use of sampling weights, and corrected
variance estimation.

Michael Sachs

eventglm

Regression Models for Event History Outcomes

Michael C Sachs

Erin E Gabriel

Morten Overgaard

Thomas A Gerds

Terry Therneau

summary.pseudoglm function

<dl><dt>object</dt>
<dd>A pseudoglm object, as returned by cumincglm or rmeanglm</dd>
<dt>correlation</dt>
<dd>logical; if TRUE, the correlation matrix of the estimated parameters is returned and printed.</dd>
<dt>symbolic.cor</dt>
<dd>logical; If TRUE, print the correlations in a symbolic form rather than as numbers.</dd>
<dt>type</dt>
<dd>The method to use for variance estimation; one of "corrected", "robust", "naive", or "cluster"</dd>
<dt>...</dt>
<dd>Not used</dd></dl>

Arguments

Summary method — summary.pseudoglm

<dl>

<dt>object</dt>
<dd>A pseudoglm object, as returned by cumincglm or rmeanglm</dd>


<dt>correlation</dt>
<dd>logical; if TRUE, the correlation matrix of the estimated parameters is returned and printed.</dd>


<dt>symbolic.cor</dt>
<dd>logical; If TRUE, print the correlations in a symbolic form rather than as numbers.</dd>


<dt>type</dt>
<dd>The method to use for variance estimation; one of "corrected", "robust", "naive", or "cluster"</dd>


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

</dl>

Summary method

summary.pseudoglm: Summary method

Description

Usage

Value

Arguments