assign_df

Determine the number of unique values in a variable. To be used in <code>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

assign_df function

<dl><dt>x</dt>
<dd>input matrix.</dd>
<dt>df_default</dt>
<dd>default df to be used. Default is 4.</dd></dl>

Arguments

Helper to assign degrees of freedom — assign_df

<dl>

<dt>x</dt>
<dd>input matrix.</dd>


<dt>df_default</dt>
<dd>default df to be used. Default is 4.</dd>

</dl>

assign_df: Helper to assign degrees of freedom

Description

Usage

Value

Arguments

Details

Examples