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mets (version 0.2.5)

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)

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Install

install.packages('mets')

Monthly Downloads

19,799

Version

0.2.5

License

GPL (>= 2)

Maintainer

Klaus K Holst

Last Published

December 16th, 2013

Functions in mets (0.2.5)

fast.approx

Fast approximation
Grandom.cif

Additive Random effects model for competing risks data for polygenetic modelling
fast.pattern

Fast pattern
twinlm

Classic twin model for quantitative traits
Dbvn

Derivatives of the bivariate normal cumulative distribution function
bptwin

Liability model for twin data
printcasewisetest

prints Concordance test
lifetable

Life table
npc

For internal use
np

np data set
simClaytonOakesWei

Simulate from the Clayton-Oakes frailty model
multcif

Multivariate Cumulative Incidence Function example data set
dermalridgesMZ

Dermal ridges data (monozygotic twins)
plack.cif

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

Stutter data set
simClaytonOakes

Simulate from the Clayton-Oakes frailty model
test.conc

Concordance test Compares two concordance estimates
casewise

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

Menarche data set
ClaytonOakes

Clayton-Oakes model with piece-wise constant hazards
mets-package

Analysis of Multivariate Events
twinsim

Simulate twin data
aalenfrailty

Aalen frailty model
summary.cor

Summary for dependence models for competing risks
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.
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.
random.cif

Random effects model for competing risks data
phreg

Fast Cox PH regression
twinbmi

BMI data set
concordance

Concordance Computes concordance and probandwise concordance
ipw

Inverse Probability of Censoring Weights
migr

Migraine data
dermalridges

Dermal ridges data (families)
simAalenFrailty

Simulate from the Aalen Frailty model
prt

Prostate data set
easy.twostage

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.
twostage

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.
back2timereg

Convert to timereg object
bicomprisk

Estimation of concordance in bivariate competing risks data
fast.reshape

Fast reshape Simple reshape/tranpose of data
casewise.test

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

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