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mets (version 1.2.5)

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) . 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

19,799

Version

1.2.5

License

GPL (>= 2)

Issues

3

Pull Requests

0

Stars

14

Forks

5

Maintainer

Klaus Holst

Last Published

November 20th, 2018

Functions in mets (1.2.5)

LinSpline

Simple linear spline
EVaddGam

Relative risk for additive gamma model
Grandom.cif

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

Concordance Computes concordance and casewise concordance
aalenfrailty

Aalen frailty model
blocksample

Block sampling
cor.cif

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

Liability model for twin data
biprobit

Bivariate Probit model
dspline

Simple linear spline
dtable

tables for data frames
easy.survival.twostage

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

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

Extract survival estimates from lifetable analysis
dermalridges

Dermal ridges data (families)
covarianceRecurrent

Estimation of covariance for bivariate recurrent events with terminal event
ipw2

Inverse Probability of Censoring Weights
plack.cif

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

Kaplan-Meier with robust standard errors
pmvn

Multivariate normal distribution function
dermalridgesMZ

Dermal ridges data (monozygotic twins)
random.cif

Random effects model for competing risks data
recurrentMarginal

Fast recurrent marginal mean when death is possible
dlag

Lag operator
ClaytonOakes

Clayton-Oakes model with piece-wise constant hazards
dprint

list, head, print, tail
familycluster.index

Finds all pairs within a cluster (family)
back2timereg

Convert to timereg object
drelevel

relev levels for data frames
test.conc

Concordance test Compares two concordance estimates
dsort

Sort data frame
base1cumhaz

rate of CRBSI for HPN patients of Copenhagen
familyclusterWithProbands.index

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

Derivatives of the bivariate normal cumulative distribution function
basehazplot.phreg

Plotting the baslines of stratified Cox
bicomprisk

Estimation of concordance in bivariate competing risks data
dcor

summary, tables, and correlations for data frames
cif

Cumulative incidence with robust standard errors
dtransform

Transform that allows condition
dcut

Cutting, sorting, rm (removing), rename for data frames
lifetable.matrix

Life table
lifecourse

Life-course plot
npc

For internal use
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.
phreg

Fast Cox PH regression
drcumhaz

Rate for leaving HPN program for patients of Copenhagen
np

np data set
dreg

Regression for data frames with dutility call
cluster.index

Finds subjects related to same cluster
fast.reshape

Fast reshape
tetrachoric

Estimate parameters from odds-ratio
ipw

Inverse Probability of Censoring Weights
daggregate

aggregating for for data frames
prob.exceed.recurrent

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

Stutter data set
multcif

Multivariate Cumulative Incidence Function example data set
migr

Migraine data
prt

Prostate data set
simClaytonOakesWei

Simulate from the Clayton-Oakes frailty model
twostageMLE

Twostage survival model fitted by pseudo MLE
simRecurrent

Simulation of recurrent events data based on cumulative hazards
survival.iterative

Survival model for multivariate survival data
dby

Calculate summary statistics grouped by
gof.phreg

GOF for Cox PH regression
gofG.phreg

Stratified baseline graphical GOF test for Cox covariates in PH regression
divide.conquer.timereg

Split a data set and run function from timereg and aggregate
survival.twostage

Twostage survival model for multivariate survival data
divide.conquer

Split a data set and run function
fast.approx

Fast approximation
fast.pattern

Fast pattern
logitSurv

Proportional odds survival model
gofM.phreg

GOF for Cox covariates in PH regression
mena

Menarche data set
predict.phreg

Predictions from proportional hazards model
mets-package

Analysis of Multivariate Events
print.casewise

prints Concordance test
simAalenFrailty

Simulate from the Aalen Frailty model
simRecurrentII

Simulation of recurrent events data based on cumulative hazards II
mets.options

Set global options for mets
simClaytonOakes

Simulate from the Clayton-Oakes frailty model
summary.cor

Summary for dependence models for competing risks
twinlm

Classic twin model for quantitative traits
twinsim

Simulate twin data
twin.clustertrunc

Estimation of twostage model with cluster truncation in bivariate situation
twinbmi

BMI data set