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>. 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).

Version:	1.3.2
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:	2023-01-17
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
SystemRequirements:	C++11
Citation:	mets citation info
Materials:	README NEWS
In views:	Survival
CRAN checks:	mets results

Documentation:

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 Binomial Regression Cumulative Incidence Regression 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

Downloads:

Package source:	mets_1.3.2.tar.gz
Windows binaries:	r-devel: mets_1.3.2.zip, r-release: mets_1.3.2.zip, r-oldrel: mets_1.3.2.zip
macOS binaries:	r-release (arm64): mets_1.3.2.tgz, r-oldrel (arm64): mets_1.3.2.tgz, r-release (x86_64): mets_1.3.2.tgz, r-oldrel (x86_64): mets_1.3.2.tgz
Old sources:	mets archive

Reverse dependencies:

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

Linking:

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