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

## S3 method for class 'casewise'
print(x, digits = 3, ...)

<table summary="R argblock">
<tr valign="top">
<td><code>x</code></td>
<td>
<p>output from casewise.test</p>
</td>
</tr>
<tr valign="top">
<td><code>digits</code></td>
<td>
<p>number of digits</p>
</td>
</tr>
<tr valign="top">
<td><code>...</code></td>
<td>
<p>Additional arguments to lower level functions</p>
</td>
</tr>
</table>

package-ubuntu-20.04-r-4.0.5#cran#mets-1.2.8.1#docs#print.casewise

print.casewise

Description

Usage

Arguments

Author(s)

mets

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`x`	output from casewise.test
`digits`	number of digits
`...`	Additional arguments to lower level functions