pssm (version 1.1.1)

pssm.survivalcurv: time to progression and time to death function for a "pssm" object

Description

Generates a function of time for specified covariate values from a "pssm" object created by pssm that fits a joint proportional hazards and survival model using a piecewise exponential underlying hazard function

Usage

pssm.survivalcurv(x, cov1, cov2, timeToProgression = FALSE, covariance = TRUE)

Arguments

x

A pssm object created by pssm

cov1

a \(a*b\) matrix of values of the \(b\) covariates affecting the time to progession

cov2

a matrix of values of the covariates affecting survival after progression with the same number of rows as cov1

timeToProgression

if FALSE estimates the survival curve, if TRUE estimates two probabilities, the probability of being disease free before t and the probability of progressing before t but surviving after t

covariance

if TRUE the covariance matrix is returned as an attribute of the function value

Value

A function is returned, the input to the function is a vector of times, and an optional parameter indicating the prior precision on the estimate of the -log hazard ratio of the effect of survival after progression on the last covariate in the survival model (presumed to be treatment) and the output is a data frame with columns described below:

Note that to conduct the bayesian analysis the Covariance needs to be set to T.

rep

indicates what is estimated (see below), values are "s1" or "s2"

time

Time, \(t\)

covariates

Columns indicating covariates for survival and progression

estimate

Estimate, If timeToProgession is TRUE and the estimation was done with both survival and time to progession the "s1" value is the probability that a patient will progress before time \(t\) but survive longer than \(t\). In that case the value at "s2" is the probability a patient will be disease free before \(t\). Otherwise rep will only equal "s1" and it will be the probability that survival or progression occurs latter than \(t\) as the case may be.

Details

pssm.survivalcurv returns a function the argument of which is the vector of times for which survival probabilities are desired.

See Also

pssm-class, pssm-package, pssm.generate.data, pssm.object, pssm, pssm.simulate,

plot-methods, pssm.power

Examples

# NOT RUN {
#generate data for plot
u<-pssm.generate.data(theta1=.5,theta2=0,phaz.progression=rep(log(-log(.3)/4),5),	
    phaz.survival=rep(log(-log(.15)/4),15),accrual=2,followup=2.9,m=5,
    n=50,times=c(1,2,3),delta=0.5)
#estimate parameters
ps<-pssm(surv(tprog0,tprog1)~rx,surv(tdeath,cdeath)~rx,dat=u,intervals=3)
#calculate survival curves
vs<-pssm.survivalcurv(ps,cov1=matrix(c(0,1),2,1),cov2=matrix(c(0,1),2,1),covariance=TRUE)
t=c(0,2,4,4.99)
curves=vs(t)
#plot survival curves
plot(t,curves$estimate[curves$rx==0],type='l',lty=2,ylim=c(0,1),
     main='Survival Curve',xlab='Time',ylab='Probability of Survival')
points(t,curves$estimate[curves$rx==1],type='l',lty=1,xlim=c(0,5))
# }