pssm.generate.data: Generates data with a piecewise exponential proportional...

In pssm: Piecewise Exponential Model for Time to Progression and Time from Progression to Death

Description

Generates data for the pssm model

Usage

pssm.generate.data(theta1 = 0.2, theta2 = 0.2, 
phaz.progression = log(-log(0.3)/4) * rep(1, 5), 
phaz.survival = log(-log(0.15)/4) * rep(1, 15), accrual = 3, 
followup = 2, m = 5, n = 400, times = NULL, delta = 0.15,alloc=c(1,1),seed=NULL)

Arguments

theta1	Coefficient for treatment covariate for time to progression
theta2	Coefficient for treatment covariate for survival after progression
phaz.progression	log-hazard vector for progression
phaz.survival	log-hazard vector for survival
accrual	accrual time
followup	follow up time
m	number of intervals, maximum of times
n	number of samples
times	vector of planned times that progression is assessed, if NULL delta isn't used and times are between (2*i-1)*m/8, (2*(i+1)-1)*m/8 for i=1,...,m-2
delta	variation around the assessment times
alloc	Allocation between control and treatment group c(1,1) is one to one allocation.
seed	Seed for the random number generator if you don't want the data that is analyzed to change.

Value

Data frame tprog0,tprog1,cdeath,tdeath,rx=c(rep(0,n/2),rep(1,n/2)

tprog0	Last time the patient was free of progressive disease
tprog1	First time progressive disease was noted, NA if no progression
cdeath	1 if the patient died, 0 otherwise
tdeath	Time of death or last follow up
rx	Treatment indicator a covariate which is 0 or 1

Author(s)

David Schoenfeld

See Also

pssm-class, pssm-package, pssm.object pssm, pssm.simulate, pssm.survivalcurv plot-methods pssm.power

Examples

##---- Should be DIRECTLY executable !! ----
##-- ==>  Define data, use random,
##--	or do  help(data=index)  for the standard data sets.
u=pssm.generate.data(theta1=.5,theta2=0,phaz.progression=rep(log(-log(.3)/4),5),	
phaz.survival=rep(log(-log(.2)/4),15),accrual=2,followup=2.9,m=5,n=300,times=c(.8,2.1,3.4))

pssm documentation built on May 2, 2019, 11:12 a.m.