.modelfit

Use update function to refit model and extract info such as coef, logLik and
estfun.

Model-based trees for subgroup analyses in clinical trials and
model-based forests for the estimation and prediction of personalised
treatment effects (personalised models). Currently partitioning of linear
models, lm(), generalised linear models, glm(), and Weibull models,
survreg(), is supported. Advanced plotting functionality is supported for
the trees and a test for parameter heterogeneity is provided for the
personalised models. For details on model-based trees for subgroup analyses
see Seibold, Zeileis and Hothorn (2016) <doi:10.1515/ijb-2015-0032>; for
details on model-based forests for estimation of individual treatment effects
see Seibold, Zeileis and Hothorn (2017) <doi:10.1177/0962280217693034>.

Heidi Seibold

model4you

Stratified and Personalised Models Based on Model-Based Trees
and Forests

Achim Zeileis

Torsten Hothorn

.modelfit function

<dl><dt>model</dt>
<dd>model object.</dd>
<dt>data</dt>
<dd>data.</dd>
<dt>coeffun</dt>
<dd>function that takes the model object and returns the coefficients.
Useful when coef() does not return all coefficients (e.g. survreg).</dd>
<dt>weights</dt>
<dd>weights.</dd>
<dt>control</dt>
<dd>control options from <code>ctree_control</code>.</dd>
<dt>parm</dt>
<dd>which parameters should be used for instability test?</dd></dl>

Arguments

Fit function when model object is given — .modelfit

<dl>

<dt>model</dt>
<dd>model object.</dd>


<dt>data</dt>
<dd>data.</dd>


<dt>coeffun</dt>
<dd>function that takes the model object and returns the coefficients.
Useful when coef() does not return all coefficients (e.g. survreg).</dd>


<dt>weights</dt>
<dd>weights.</dd>


<dt>control</dt>
<dd>control options from <code>ctree_control</code>.</dd>


<dt>parm</dt>
<dd>which parameters should be used for instability test?</dd>

</dl>

.modelfit: Fit function when model object is given

Description

Usage

Value

Arguments