pool_pamm_fits

Combines the <code>m</code> imputation fits with Rubin's rules: the pooled
parametric coefficients use \(\bar Q\) and
\(V = \bar W + (1 + 1/m) B\). Smooth-term p-values are pooled with the
median-p rule (see references in <code>strip_pamm_fit</code>). Because
<code>mgcv</code> smooth coefficients can use different centered bases across
imputations, this returns a plain pooled summary object rather than a
<code>gam</code>: <code>add_*()</code> methods evaluate every imputation fit with its own
design matrix for predictions.

internal

The Piece-wise exponential (Additive Mixed) Model
(PAMM; Bender and others (2018) <doi: 10.1177/1471082X17748083>) is a
powerful model class for the analysis of survival (or time-to-event) data,
based on Generalized Additive (Mixed) Models (GA(M)Ms).
It offers intuitive specification and robust estimation of complex survival
models with stratified baseline hazards, random effects, time-varying effects,
time-dependent covariates and cumulative effects (Bender and others (2019)),
as well as support for left-truncated data as well as competing risks,
recurrent events and multi-state settings.
pammtools provides tidy workflow for survival analysis with PAMMs,
including data simulation, transformation and other functions for data
preprocessing and model post-processing as well as visualization.

Andreas Bender

pammtools

Piece-Wise Exponential Additive Mixed Modeling Tools for
Survival Analysis

Fabian Scheipl

Johannes Piller

Philipp Kopper

Lukas Burk

pool_pamm_fits function

<dl><dt>fits</dt>
<dd>List of stripped imputation fits.</dd>
<dt>smry</dt>
<dd>List of <code>summary.gam</code> objects, one per fit (computed before
stripping).</dd>
<dt>skeleton</dt>
<dd>Optional full (unstripped) fit used only to supply a common
training-grid model frame for smooth-term FMI summaries.</dd></dl>

Arguments

Pool a list of (stripped) imputation fits into a pooled summary object — pool_pamm_fits

<dl>

<dt>fits</dt>
<dd>List of stripped imputation fits.</dd>


<dt>smry</dt>
<dd>List of <code>summary.gam</code> objects, one per fit (computed before
stripping).</dd>


<dt>skeleton</dt>
<dd>Optional full (unstripped) fit used only to supply a common
training-grid model frame for smooth-term FMI summaries.</dd>

</dl>

pool_pamm_fits: Pool a list of (stripped) imputation fits into a pooled summary object

Description

Usage

Arguments