All functions

BinAugmentCifstrata()

Augmentation for Binomial regression based on stratified NPMLE Cif (Aalen-Johansen)

Bootphreg()

Wild bootstrap for Cox PH regression

ClaytonOakes()

Clayton-Oakes model with piece-wise constant hazards

Dbvn()

Derivatives of the bivariate normal cumulative distribution function

EVaddGam()

Relative risk for additive gamma model

FG_AugmentCifstrata()

Augmentation for Fine-Gray model based on stratified NPMLE Cif (Aalen-Johansen)

Grandom.cif()

Additive Random effects model for competing risks data for polygenetic modelling

LinSpline()

Simple linear spline

aalenfrailty()

Aalen frailty model

back2timereg()

Convert to timereg object

base1cumhaz

rate of CRBSI for HPN patients of Copenhagen

base44cumhaz

rate of Occlusion/Thrombosis complication for catheter of HPN patients of Copenhagen

base4cumhaz

rate of Mechanical (hole/defect) complication for catheter of HPN patients of Copenhagen

basehazplot.phreg()

Plotting the baslines of stratified Cox

bicomprisk()

Estimation of concordance in bivariate competing risks 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.

binreg()

Binomial Regression for censored competing risks data

biprobit()

Bivariate Probit model

blocksample()

Block sampling

bptwin()

Liability model for twin data

casewise()

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

casewise.test()

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

cif()

Cumulative incidence with robust standard errors

cifreg()

CIF regression

cluster.index()

Finds subjects related to same cluster

concordanceCor()

Concordance Computes concordance and casewise concordance

cor.cif()

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

count.history()

Counts the number of previous events of two types for recurrent events processes

covarianceRecurrent()

Estimation of covariance for bivariate recurrent events with terminal event

daggregate()

aggregating for for data frames

dby()

Calculate summary statistics grouped by

dcor()

summary, tables, and correlations for data frames

dcut()

Cutting, sorting, rm (removing), rename for data frames

dermalridges

Dermal ridges data (families)

dermalridgesMZ

Dermal ridges data (monozygotic twins)

divide.conquer()

Split a data set and run function

divide.conquer.timereg()

Split a data set and run function from timereg and aggregate

dlag()

Lag operator

doubleFGR()

Double CIF Fine-Gray model with two causes

dprint()

list, head, print, tail

drcumhaz

Rate for leaving HPN program for patients of Copenhagen

dreg()

Regression for data frames with dutility call

drelevel()

relev levels for data frames

dsort()

Sort data frame

dspline()

Simple linear spline

dtable()

tables for data frames

dtransform()

Transform that allows condition

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.

easy.survival.twostage()

Wrapper for easy fitting of Clayton-Oakes or bivariate Plackett models for bivariate survival data

eventpois()

Extract survival estimates from lifetable analysis

familycluster.index()

Finds all pairs within a cluster (family)

familyclusterWithProbands.index()

Finds all pairs within a cluster (famly) with the proband (case/control)

fast.approx()

Fast approximation

fast.pattern()

Fast pattern

fast.reshape()

Fast reshape

ghaplos

ghaplos haplo-types for subjects of haploX data

gof(<phreg>)

GOF for Cox PH regression

gofG.phreg()

Stratified baseline graphical GOF test for Cox covariates in PH regression

gofM.phreg()

GOF for Cox covariates in PH regression

gofZ.phreg()

GOF for Cox covariates in PH regression

hapfreqs

hapfreqs data set

haplo.surv.discrete()

Discrete time to event haplo type analysis

haploX

haploX covariates and response for haplo survival discrete survival

npc

For internal use

interval.logitsurv.discrete()

Discrete time to event interval censored data

ipw()

Inverse Probability of Censoring Weights

ipw2()

Inverse Probability of Censoring Weights

km()

Kaplan-Meier with robust standard errors

lifecourse()

Life-course plot

lifetable(<matrix>) lifetable(<formula>)

Life table

logitSurv()

Proportional odds survival model

mena

Menarche data set

mets-package

Analysis of Multivariate Events

mets.options()

Set global options for mets

migr

Migraine data

mlogit()

Multinomial regression based on phreg regression

multcif

Multivariate Cumulative Incidence Function example data set

np

np data set

phreg()

Fast Cox PH regression

phregR()

Fast Cox PH regression and calculations done in R to make play and adjustments easy

plack.cif()

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

pmvn()

Multivariate normal distribution function

predict(<phreg>)

Predictions from proportional hazards model

print(<casewise>)

prints Concordance test

prob.exceed.recurrent()

Estimation of probability of more that k events for recurrent events process

prt

Prostate data set

random.cif()

Random effects model for competing risks data

recurrentMarginal()

Fast recurrent marginal mean when death is possible

rpch()

Piecewise constant hazard distribution

simAalenFrailty()

Simulate from the Aalen Frailty model

simClaytonOakes()

Simulate from the Clayton-Oakes frailty model

simClaytonOakesWei()

Simulate from the Clayton-Oakes frailty model

simMultistate()

Simulation of illness-death model

simRecurrent()

Simulation of recurrent events data based on cumulative hazards

simRecurrentII()

Simulation of recurrent events data based on cumulative hazards II

simRecurrentTS()

Simulation of recurrent events data based on cumulative hazards: Two-stage model

summary(<cor>)

Summary for dependence models for competing risks

survival.iterative()

Survival model for multivariate survival data

survival.twostage()

Twostage survival model for multivariate survival data

test.conc()

Concordance test Compares two concordance estimates

tetrachoric()

Estimate parameters from odds-ratio

ttpd

ttpd discrete survival data on interval form

twin.clustertrunc()

Estimation of twostage model with cluster truncation in bivariate situation

twinbmi

BMI data set

twinlm()

Classic twin model for quantitative traits

twinsim()

Simulate twin data

twinstut

Stutter data set

twostageMLE()

Twostage survival model fitted by pseudo MLE