The "SurvivalModel" Class

Description

A SurvivalModel class represents the information for simulating survival times for each patient.

Usage

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SurvivalModel(baseHazard=1/5,
              accrual=5,
              followUp=1,
              units=12,
              unitName="months")
## S4 method for signature 'SurvivalModel'
rand(object, n, beta=NULL, ...) 

Arguments

baseHazard

numeric scalar describing the underlying hazard rate at baseline levels of covariates

accrual

numeric scalar representing number of patient accrual years

followUp

numeric scalar representing frequency of follow up in the unit of year

units

numeric scalar representing number of units per year where units are specified by unitName

unitName

character string representing the unit argument type

object

object of class SurvivalModel

n

numeric scalar specifying quantity of random numbers

beta

numeric vector specifying beta parameters for patients

...

extra arguments for generic routines

Value

The SurvivalModel generator returns an object of class SurvivalModel.

The rand method returns a data.frame with components:

LFU

time to event

Event

whether the data is censored

Objects from the Class

Although objects of the class can be created by a direct call to new, the preferred method is to use the SurvivalModel generator function.

Slots

baseHazard:

see corresponding argument above

accrual:

see corresponding argument above

followUp:

see corresponding argument above

units:

see corresponding argument above

unitName:

see corresponding argument above

Methods

rand(object, n, beta, ...)

Simulate survival data for n patients given beta.

Author(s)

Kevin R. Coombes krc@silicovore.com, Jiexin Zhang jiexinzhang@mdanderson.org, P. Roebuck proebuck@mdanderson.org

References

OOMPA

See Also

CancerModel

Examples

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showClass("SurvivalModel")
sm <- SurvivalModel()
## Generate data from base model
outcome <- rand(sm, 100)
summary(outcome)
## Generate data from five classes with different beta parameters
beta <- rep(rnorm(5, 0, 2), each=20)
outcome <- rand(sm, 100, beta=beta)
summary(outcome)