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timereg (version 1.9.8)

Flexible Regression Models for Survival Data

Description

Programs for Martinussen and Scheike (2006), `Dynamic Regression Models for Survival Data', Springer Verlag. Plus more recent developments. Additive survival model, semiparametric proportional odds model, fast cumulative residuals, excess risk models and more. Flexible competing risks regression including GOF-tests. Two-stage frailty modelling. PLS for the additive risk model. Lasso in the 'ahaz' package.

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Install

install.packages('timereg')

Monthly Downloads

8,972

Version

1.9.8

License

GPL (>= 2)

Issues

8

Pull Requests

0

Stars

33

Forks

5

Maintainer

Thomas Scheike

Last Published

October 5th, 2020

Functions in timereg (1.9.8)

cd4

The multicenter AIDS cohort study
dynreg

Fit time-varying regression model
TRACE

The TRACE study group of myocardial infarction
aalen

Fit additive hazards model
comp.risk

Competings Risks Regression
krylow.pls

Fits Krylow based PLS for additive hazards model
invsubdist

Finds inverse of piecwise linear sub-distribution
cox

Identifies proportional excess terms of model
pval

For internal use
mela.pop

Melanoma data and Danish population mortality by age and sex
cox.ipw

Missing data IPW Cox
cox.aalen

Fit Cox-Aalen survival model
csl

CSL liver chirrosis data
prop.odds

Fit Semiparametric Proportional 0dds Model
plot.dynreg

Plots estimates and test-processes
cum.residuals

Model validation based on cumulative residuals
const

Identifies parametric terms of model
prop.odds.subdist

Fit Semiparametric Proportional 0dds Model for the competing risks subdistribution
sim.cox

Simulation of output from Cox model.
event.split

EventSplit (SurvSplit).
sim.cif

Simulation of output from Cumulative incidence regression model
prep.comp.risk

Set up weights for delayed-entry competing risks data for comp.risk function
predict.timereg

Predictions for Survival and Competings Risks Regression for timereg
pava.pred

Make predictions of predict functions in rows mononotone
diabetes

The Diabetic Retinopathy Data
qcut

Cut a variable
pe.sasieni

Fits Proportional excess hazards model with fixed offsets
prop

Identifies the multiplicative terms in Cox-Aalen model and proportional excess risk model
mypbc

my version of the PBC data of the survival package
recurrent.marginal.mean

Estimates marginal mean of recurrent events
print.aalen

Prints call
melanoma

The Melanoma Survival Data
res.mean

Residual mean life (restricted)
sim.cause.cox

Simulation of cause specific from Cox models.
prop.excess

Fits Proportional excess hazards model
restricted.residual.mean

Estimates restricted residual mean for Cox or Aalen model
summary.cum.residuals

Prints summary statistics for goodness-of-fit tests based on cumulative residuals
timecox

Fit Cox model with partly timevarying effects.
rchaz

Simulation of Piecewise constant hazard model (Cox).
two.stage

Fit Clayton-Oakes-Glidden Two-Stage model
Event

Event history object
Gprop.odds

Fit Generalized Semiparametric Proportional 0dds Model
wald.test

Makes wald test
plot.cum.residuals

Plots cumulative residuals
plot.aalen

Plots estimates and test-processes
rcrisk

Simulation of Piecewise constant hazard models with two causes (Cox).
recurrent.marginal.coxmean

Estimates marginal mean of recurrent events based on two cox models
simsubdist

Simulation from subdistribution function assuming piecwise linearity
summary.aalen

Prints summary statistics
bmt

The Bone Marrow Transplant Data