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>.
Also contains two-stage binomial modelling that can do pairwise odds-ratio
dependence modelling based marginal logistic regression models. This is an
alternative to the alternating logistic regression approach (ALR).

Analysis of Multivariate Event Times

package-ubuntu-20.04-r-4.0.5#cran#mets-1.2.8.1

<p>Piecewise constant hazard distribution
</p>

<table summary="R argblock">
<tr valign="top">
<td><code>n</code></td>
<td>
<p>sample size</p>
</td>
</tr>
<tr valign="top">
<td><code>lambda</code></td>
<td>
<p>rate parameters</p>
</td>
</tr>
<tr valign="top">
<td><code>breaks</code></td>
<td>
<p>time cut-points</p>
</td>
</tr>
</table>

package-ubuntu-20.04-r-4.0.5#cran#mets-1.2.8.1#docs#rpch

rpch

Description

Usage

Arguments

mets

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`n`	sample size
`lambda`	rate parameters
`breaks`	time cut-points