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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.
Getting started
Package overview
README.md
Analysis of bivariate binomial data: Twin analysis
Analysis of multivariate binomial data: family analysis
Analysis of multivariate survival data
A practical guide to Human Genetics with Lifetime Data
Average treatment effect (ATE) for Competing risks and binary outcomes
Average treatment effect (ATE) for Restricted mean survival and years lost of Competing risks
Binomial Regression for Survival and Competing Risks Data
Cumulative Incidence Regression
Discrete Interval Censored Survival Models
dUtility data-frame manipulations
G-Computation or standardization for the Cox, Fine-Gray and binomial regression models for survival data
GEE cluster standard errors and predictions for glm objects
Haplotype Discrete Survival Models
Marginal modelling of clustered survival data
Mediation Analysis for survival data
Recurrent events
Twin models
Browse package contents
Package details |
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| Author | Klaus K. Holst [aut, cre], Thomas Scheike [aut] |
| Maintainer | Klaus K. Holst <klaus@holst.it> |
| License | GPL (>= 2) |
| Version | 1.3.4 |
| URL | https://kkholst.github.io/mets/ |
| Package repository | View on CRAN |
| Installation |
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