BinAugmentCifstrata()

Augmentation for Binomial regression based on stratified NPMLE Cif (AalenJohansen) 
Bootphreg()

Wild bootstrap for Cox PH regression 
ClaytonOakes()

ClaytonOakes model with piecewise constant hazards 
Dbvn()

Derivatives of the bivariate normal cumulative distribution function 
EVaddGam()

Relative risk for additive gamma model 
FG_AugmentCifstrata()

Augmentation for FineGray model based on stratified NPMLE Cif (AalenJohansen) 
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 ClaytonOakes 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()

Crossoddsratio, 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 FineGray 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 twostage 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 ClaytonOakes 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 haplotypes 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()

KaplanMeier with robust standard errors 
lifecourse()

Lifecourse plot 
lifetable(<matrix>) lifetable(<formula>)

Life table 
logitSurv()

Proportional odds survival model 
mena

Menarche data set 
metspackage

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 ClaytonOakes frailty model 
simClaytonOakesWei()

Simulate from the ClaytonOakes frailty model 
simMultistate()

Simulation of illnessdeath 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: Twostage 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 oddsratio 
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 