plotcr

nonparcuminc

simnordic

corsim.prostate

alpha2kendall

alpha2spear

coefmat

piecewise.twostage

surv.boxarea

faster.reshape

piecewise.data

simBinPlack

simBinFam

simBinFam2

simSurvFam

corsim.prostate.random

simnordic.random

simCox

grouptable

jumptimes

folds

ace.family.design

ascertained.pairs

CCbinomial.twostage

coarse.clust

concordanceTwinACE

concordanceTwostage

fast.cluster

force.same.cens

ilap

kendall.ClaytonOakes.twin.ace

kendall.normal.twin.ace

make.pairwise.design

make.pairwise.design.competing

matplot.mets.twostage

object.defined

p11.binomial.twostage.RV

predictPairPlack

simbinClaytonOakes.family.ace

simbinClaytonOakes.pairs

simbinClaytonOakes.twin.ace

simClaytonOakes.family.ace

simClaytonOakes.twin.ace

simFrailty.simple

simCompete.simple

simCompete.twin.ace

twin.polygen.design

procform

procform3

procformdata

drop.specials

utilities

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.

npc: For internal use

Description

Arguments

Author