LinSpline

survival

Implementation of various statistical models for multivariate
event history data <doi:10.1007/s10985-013-9244-x>. Including multivariate
cumulative incidence models <doi:10.1002/sim.6016>, and bivariate random
effects probit models (Liability models) <doi:10.1016/j.csda.2015.01.014>.
Modern methods for survival analysis, including regression modelling (Cox, Fine-Gray,
Ghosh-Lin, Binomial regression) with fast computation of influence functions.

Klaus Holst

mets

Analysis of Multivariate Event Times

Klaus K. Holst

Thomas Scheike 

LinSpline function

<dl><dt>x</dt>
<dd>variable to make into spline</dd>
<dt>knots</dt>
<dd>cut points</dd>
<dt>num</dt>
<dd>to give names x1 x2 and so forth</dd>
<dt>name</dt>
<dd>name of spline expansion name.1 name.2 and so forth</dd></dl>

Arguments

Author

Simple linear spline — LinSpline

<dl>

<dt>x</dt>
<dd>variable to make into spline</dd>


<dt>knots</dt>
<dd>cut points</dd>


<dt>num</dt>
<dd>to give names x1 x2 and so forth</dd>


<dt>name</dt>
<dd>name of spline expansion name.1 name.2 and so forth</dd>

</dl>

Simple linear spline

LinSpline: Simple linear spline

Description

Usage

Arguments

Author