mets: Analysis of Multivariate Event Times

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.

Version: 1.3.4
Depends: R (≥ 3.5), timereg (≥ 1.9.4)
Imports: lava (≥ 1.7.1), mvtnorm, numDeriv, compiler, Rcpp, splines, survival (≥ 2.43-1)
LinkingTo: Rcpp, RcppArmadillo, mvtnorm
Suggests: optimx, prodlim, cmprsk, testthat (≥ 0.11), ucminf, knitr, rmarkdown, ggplot2, cowplot, icenReg
Published: 2024-02-16
DOI: 10.32614/CRAN.package.mets
Author: Klaus K. Holst [aut, cre], Thomas Scheike [aut]
Maintainer: Klaus K. Holst <klaus at>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: yes
Citation: mets citation info
Materials: README NEWS
In views: Survival
CRAN checks: mets results


Reference manual: mets.pdf
Vignettes: dUtility data-frame manipulations
Analysis of multivariate binomial data: family analysis
Analysis of bivariate binomial data: Twin analysis
Average treatment effect (ATE) for Competing risks and binary outcomes
Two-Stage Randomization for for Competing risks and Survival outcomes
Binomial Regression for Survival and Competing Risks Data
Cumulative Incidence Regression
GEE cluster standard errors and predictions for glm objects
Haplotype Discrete Survival Models
Discrete Interval Censored Survival Models
Marginal modelling of clustered survival data
Mediation Analysis for survival data
Twin models
Recurrent events
Average treatment effect (ATE) for Restricted mean survival and years lost of Competing risks
Average treatment effect (ATE) based on the Cox and Fine-Gray model
A practical guide to Human Genetics with Lifetime Data
Analysis of multivariate survival data


Package source: mets_1.3.4.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): mets_1.3.4.tgz, r-oldrel (arm64): mets_1.3.4.tgz, r-release (x86_64): mets_1.3.4.tgz, r-oldrel (x86_64): mets_1.3.4.tgz
Old sources: mets archive

Reverse dependencies:

Reverse imports: riskRegression, targeted
Reverse suggests: lava, mmcif, timereg


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