prepare_newdata_for_predict

To be used in <code>predict.mfp2()</code>.

Multivariable fractional polynomial algorithm simultaneously selects variables and functional forms in both generalized linear models and Cox proportional hazard models. Key references for this algorithm are Royston and Altman (1994)<doi:10.2307/2986270> and Sauerbrei and Royston (2008, ISBN:978-0-470-02842-1). In addition, it can model a 'sigmoid' relationship between variable x and an outcome variable y using the approximate cumulative distribution transformation proposed by Royston (2014) <doi:10.1177/1536867X1401400206>. This feature distinguishes it from a standard fractional polynomial function, which lacks the ability to achieve such modeling.

Edwin Kipruto

mfp2

Multivariable Fractional Polynomial Models with Extensions

Michael Kammer

Patrick Royston

Willi Sauerbrei

prepare_newdata_for_predict function

<dl><dt>object</dt>
<dd>fitted <code>mfp2</code> model object.</dd>
<dt>newdata</dt>
<dd>dataset to be prepared for predictions. Its columns can be
a subset of the columns used for fitting the model.</dd>
<dt>strata, offset</dt>
<dd>passed from <code>predict.mfp2()</code>.</dd>
<dt>apply_pre</dt>
<dd>logical indicating wether the fitted pre-transformation
is applied or not.</dd>
<dt>apply_center</dt>
<dd>logical indicating whether the fitted centers are applied
after transformation or not.</dd>
<dt>check_binary</dt>
<dd>passed to <code>transform_vector_fp()</code>.</dd></dl>

Arguments

Helper function to prepare newdata for predict function — prepare_newdata_for_predict

<dl>

<dt>object</dt>
<dd>fitted <code>mfp2</code> model object.</dd>


<dt>newdata</dt>
<dd>dataset to be prepared for predictions. Its columns can be
a subset of the columns used for fitting the model.</dd>


<dt>strata, offset</dt>
<dd>passed from <code>predict.mfp2()</code>.</dd>


<dt>apply_pre</dt>
<dd>logical indicating wether the fitted pre-transformation
is applied or not.</dd>


<dt>apply_center</dt>
<dd>logical indicating whether the fitted centers are applied
after transformation or not.</dd>


<dt>check_binary</dt>
<dd>passed to <code>transform_vector_fp()</code>.</dd>

</dl>

prepare_newdata_for_predict: Helper function to prepare newdata for predict function

Description

Usage

Value

Arguments