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: 1.3.8
Depends: R (≥ 3.5)
Imports: Rcpp, lava (≥ 1.8.1), methods, mvtnorm, numDeriv, splines, survival (≥ 2.43-1), timereg (≥ 1.9.4)
LinkingTo: Rcpp, RcppArmadillo, mvtnorm
Suggests: cmprsk, icenReg, KernSmooth, knitr, mets, optimx, prodlim, riskRegression, rmarkdown, tinytest (≥ 1.4.1), ucminf
Published: 2025-10-21
DOI: 10.32614/CRAN.package.mets
Author: Klaus K. Holst [aut, cre], Thomas Scheike [aut]
Maintainer: Klaus K. Holst <klaus at holst.it>
BugReports: https://github.com/kkholst/mets/issues
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: https://kkholst.github.io/mets/
NeedsCompilation: yes
Citation: mets citation info
Materials: README, NEWS
In views: Survival
CRAN checks: mets results

Documentation:

Reference manual: mets.html , mets.pdf
Vignettes: dUtility data-frame manipulations (source, R code)
Analysis of multivariate binomial data: family analysis (source, R code)
Analysis of bivariate binomial data: Twin analysis (source, R code)
Average treatment effect (ATE) for Competing risks and binary outcomes (source, R code)
Two-Stage Randomization for for Competing risks and Survival outcomes (source, R code)
Binomial Regression for Survival and Competing Risks Data (source, R code)
Cumulative Incidence Regression (source, R code)
Cooking survival data, 5 minutes recipes (source, R code)
GEE cluster standard errors and predictions for glm objects (source, R code)
Haplotype Discrete Survival Models (source, R code)
Discrete Interval Censored Survival Models (source, R code)
Marginal modelling of clustered survival data (source, R code)
Mediation Analysis for survival data (source, R code)
Randomization for Cox Type rate models (source, R code)
Twin models (source, R code)
Recurrent events (source, R code)
Average treatment effect (ATE) for Restricted mean survival and years lost of Competing risks (source, R code)
Average treatment effect (ATE) based on the Cox and Fine-Gray model (source, R code)
A practical guide to Human Genetics with Lifetime Data (source, R code)
Analysis of multivariate survival data (source, R code)
While Alive estimands for Recurrent Events (source, R code)

Downloads:

Package source: mets_1.3.8.tar.gz
Windows binaries: r-devel: mets_1.3.8.zip, r-release: mets_1.3.8.zip, r-oldrel: mets_1.3.8.zip
macOS binaries: r-release (arm64): mets_1.3.8.tgz, r-oldrel (arm64): mets_1.3.8.tgz, r-release (x86_64): mets_1.3.8.tgz, r-oldrel (x86_64): mets_1.3.8.tgz
Old sources: mets archive

Reverse dependencies:

Reverse imports: recforest, riskRegression, targeted
Reverse suggests: lava, mets, mmcif, polle, timereg

Linking:

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