Description Usage Arguments Value Author(s) See Also Examples
Generates data for the pssm model
1 2 3 4 |
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 |
seed |
Seed for the random number generator if you don't want the data that is analyzed to change. |
Data frame tprog0,tprog1,cdeath,tdeath,rx=c(rep(0,n/2),rep(1,n/2)
|
Last time the patient was free of progressive disease |
|
First time progressive disease was noted, NA if no progression |
|
1 if the patient died, 0 otherwise |
|
Time of death or last follow up |
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Treatment indicator a covariate which is 0 or 1 |
David Schoenfeld
pssm-class
,
pssm-package
,
pssm.object
pssm
,
pssm.simulate
,
pssm.survivalcurv
plot-methods
pssm.power
1 2 3 4 5 | ##---- 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))
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