Implementation of various statistical models for multivariate event history data. Including multivariate cumulative incidence models, and bivariate random effects probit models (Liability models). 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).

Documentation

Manual: mets.pdf
Vignette: None available.

Maintainer: Klaus K. Holst <klaus at holst.it>

Author(s): Klaus K. Holst and Thomas Scheike

Install package and any missing dependencies by running this line in your R console:

install.packages("mets")

Depends R (>= 3.3), timereg(>=1.8.9), lava(>=1.4.7)
Imports numDeriv, compiler, Rcpp, splines, survival
Suggests lava.tobit(>=0.4-7), prodlim, testthat(>=0.11), ucminf
Enhances
Linking to Rcpp, RcppArmadillo
Reverse
depends
Reverse
imports
Reverse
suggests
gap, lava, riskRegression
Reverse
enhances
Reverse
linking to

Package mets
Materials
URL https://github.com/kkholst/mets
Task Views Survival
Version 1.2.1
Published 2017-02-27
License GPL (>= 2)
BugReports
SystemRequirements
NeedsCompilation yes
Citation
CRAN checks mets check results
Package source mets_1.2.1.tar.gz