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conda-forge/r-mets

r-mets

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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).

Copied fromcf-post-staging / r-mets

Installation

To install this package, run one of the following:

Conda
$conda install conda-forge::r-mets

Usage Tracking

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About

Summary

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).

Last Updated

Jan 11, 2026 at 19:36

License

GPL-2.0-or-later

Total Downloads

71.0K

Supported Platforms

macOS-64
win-64
linux-64

Home

https://kkholst.github.io/mets/