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mets (version 1.2.4)

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).

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Install

install.packages('mets')

Monthly Downloads

9,492

Version

1.2.4

License

GPL (>= 2)

Issues

3

Pull Requests

0

Stars

15

Forks

3

Maintainer

Klaus Holst

Last Published

August 13th, 2018

Functions in mets (1.2.4)

cif

Cumulative incidence with robust standard errors
biprobit

Bivariate Probit model
lifecourse

Life-course plot
lifetable.matrix

Life table
fast.approx

Fast approximation
fast.pattern

Fast pattern
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.
np

np data set
multcif

Multivariate Cumulative Incidence Function example data set
concordance

Concordance Computes concordance and casewise concordance
aalenfrailty

Aalen frailty model
blocksample

Block sampling
bptwin

Liability model for twin data
summary.cor

Summary for dependence models for competing risks
dermalridgesMZ

Dermal ridges data (monozygotic twins)
dermalridges

Dermal ridges data (families)
cluster.index

Finds subjects related to same cluster
cor.cif

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

aggregating for for data frames
dreg

Regression for data frames with dutility call
drcumhaz

Rate for leaving HPN program for patients of Copenhagen
drelevel

relev levels for data frames
mena

Menarche data set
dby

Calculate summary statistics grouped by
dlag

Lag operator
mets-package

Analysis of Multivariate Events
dprint

list, head, print, tail
phreg

Fast Cox PH regression
familycluster.index

Finds all pairs within a cluster (family)
survival.iterative

Survival model for multivariate survival data
familyclusterWithProbands.index

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

Sort data frame
basehazplot.phreg

Plotting the baslines of stratified Cox
fast.reshape

Fast reshape
plack.cif

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

GOF for Cox PH regression
bicomprisk

Estimation of concordance in bivariate competing risks data
dcor

summary, tables, and correlations for data frames
dcut

Cutting, sorting, rm (removing), rename for data frames
divide.conquer

Split a data set and run function
simRecurrent

Simulation of recurrent events data based on cumulative hazards
casewise

Estimates the casewise concordance based on Concordance and marginal estimate using prodlim but no testing
ipw2

Inverse Probability of Censoring Weights
simRecurrentII

Simulation of recurrent events data based on cumulative hazards II
casewise.test

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

Kaplan-Meier with robust standard errors
mets.options

Set global options for mets
divide.conquer.timereg

Split a data set and run function from timereg and aggregate
gofG.phreg

Stratified baseline graphical GOF test for Cox covariates in PH regression
easy.survival.twostage

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

Migraine data
eventpois

Extract survival estimates from lifetable analysis
count.history

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

For internal use
twinsim

Simulate twin data
twinstut

Stutter data set
covarianceRecurrent

Estimation of covariance for bivariate recurrent events with terminal event
gofM.phreg

GOF for Cox covariates in PH regression
ipw

Inverse Probability of Censoring Weights
print.casewise

prints Concordance test
recurrentMarginal

Fast recurrent marginal mean when death is possible
dspline

Simple linear spline
dtable

tables for data frames
prob.exceed.recurrent

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

Simulate from the Clayton-Oakes frailty model
dtransform

Transform that allows condition
twinbmi

BMI data set
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.
simClaytonOakesWei

Simulate from the Clayton-Oakes frailty model
simAalenFrailty

Simulate from the Aalen Frailty model
twinlm

Classic twin model for quantitative traits
survival.twostage

Twostage survival model for multivariate survival data
test.conc

Concordance test Compares two concordance estimates
pmvn

Multivariate normal distribution function
predict.phreg

Predictions from proportional hazards model
prt

Prostate data set
random.cif

Random effects model for competing risks data
tetrachoric

Estimate parameters from odds-ratio
twin.clustertrunc

Estimation of twostage model with cluster truncation in bivariate situation
Dbvn

Derivatives of the bivariate normal cumulative distribution function
ClaytonOakes

Clayton-Oakes model with piece-wise constant hazards
back2timereg

Convert to timereg object
EVaddGam

Relative risk for additive gamma model
LinSpline

Simple linear spline
base44cumhaz

rate of Occlusion/Thrombosis complication for catheter of HPN patients of Copenhagen
base1cumhaz

rate of CRBSI for HPN patients of Copenhagen
Grandom.cif

Additive Random effects model for competing risks data for polygenetic modelling
base4cumhaz

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