pssm (version 1.1.1)

pssm.generate.data: Generates data with a piecewise exponential proportional hazards model for progression and surivival

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

See Also

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

Examples

# NOT RUN {
##---- 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))
# }