Learn R Programming

⚠️There's a newer version (1.3.8) of this package.Take me there.

mets (version 0.2.7)

Analysis of Multivariate Event Times

Description

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).

Copy Link

Version

Install

install.packages('mets')

Monthly Downloads

19,799

Version

0.2.7

License

GPL (>= 2)

Maintainer

Klaus K Holst

Last Published

February 20th, 2014

Functions in mets (0.2.7)

simClaytonOakesWei

Simulate from the Clayton-Oakes frailty model

Random effects model for competing risks data

Multivariate Cumulative Incidence Function example data set

For internal use

Aalen frailty model

Derivatives of the bivariate normal cumulative distribution function

Fast Cox PH regression

printcasewisetest

prints Concordance test

Estimation of concordance in bivariate competing risks data

Dermal ridges data (families)

Fits two-stage model for describing depdendence in survival data using marginals that are on cox or aalen form using the twostage funcion, but call is different and easier and the data manipulation build into the function. Useful in particular for family design data.

Dermal ridges data (monozygotic twins)

Prostate data set

Liability model for twin data

Menarche data set

Fast approximation

Concordance test Compares two concordance estimates

Liability model for twin data

simClaytonOakes

Simulate from the Clayton-Oakes frailty model

Classic twin model for quantitative traits

Estimates the casewise concordance based on Concordance and marginal estimate using prodlim but no testing

Convert to timereg object

lifetable.matrix

Estimates the casewise concordance based on Concordance and marginal estimate using timereg and performs test for independence

Summary for dependence models for competing risks

plack Computes concordance for or.cif based model, that is Plackett random effects model

Clayton-Oakes model with piece-wise constant hazards

simAalenFrailty

Simulate from the Aalen Frailty model

binomial.twostage

Fits Clayton-Oakes or bivariate Plackett (OR) models for binary data using marginals that are on logistic form. If clusters contain more than two times, the algoritm uses a compososite likelihood based on all pairwise bivariate models.

Fits Clayton-Oakes or bivariate Plackett models for bivariate survival data using marginals that are on Cox or addtive form. If clusters contain more than two times, the algoritm uses a compososite likelihood based on the pairwise bivariate models.

Stutter data set

Additive Random effects model for competing risks data for polygenetic modelling

Concordance Computes concordance and probandwise concordance

Fast reshape Simple reshape/tranpose of data

Analysis of Multivariate Events

easy.binomial.twostage

Fits two-stage binomial for describing depdendence in binomial data using marginals that are on logistic form using the binomial.twostage funcion, but call is different and easier and the data manipulation is build into the function. Useful in particular for family design data.

Cross-odds-ratio, OR or RR risk regression for competing risks

Inverse Probability of Censoring Weights

Simulate twin data