e11-SurvivalModel-class: The "SurvivalModel" Class

In Umpire: Simulating Realistic Gene Expression and Clinical Data

The "SurvivalModel" Class

Description

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

Usage

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 length of follow up, in years
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 [e-mail], Jiexin Zhang [e-mail],

References

Zhang J, Coombes KR.
Sources of variation in false discovery rate estimation include sample size, correlation, and inherent differences between groups.
BMC Bioinformatics. 2012; 13 Suppl 13:S1.

See Also

CancerModel

Examples

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)

Umpire documentation built on April 4, 2025, 5:26 a.m.