SimSurv {prodlim} | R Documentation |
Censored event times are drawn from user specified conditional distributions given simulated covariates.
SimSurv(N, surv, cens, cova, verbose=1, ...)
N |
Sample size |
surv |
Dummy argument. The survival distribution is determined by
arguments of the form surv.arg . See Details |
cens |
If FALSE data are left uncensored. Otherwise the censoring
distribution is specified by using arguments of the form
cens.arg . See Details. |
cova |
either a matrix with N rows,
or a named list to generate the covariates. each entry
is a list where the first element is the names of the
function used to draw the covariate values and the remaining
elements are arguments passed to that function. For example
cova=list(X = list(dist = "rlnorm", meanlog = 2, sdlog = 0.4))
generates a single log-normally distributed covariate called
X .
|
verbose |
Set to FALSE to shut up in simulations |
... |
used for convenient argument specification, e.g.
surv.transform.X2=function(x)x^2
will overwrite a corresponding entry
of surv for the transform of the
covariate X2
|
surv.dist
name of the function to draw the survival distribution
surv.baseline
the baseline risk
surv.link
names of the link to the covariates
surv.coef
numeric vector of regression coefficients. the ith is
used for the ith entry of cova
surv.transform
list of function names one for each covariate. the ith is applied
to values of the ith covariate before it is linked to generate the
survival times.
cens.dist
name of the function to draw the censoring distribution
cens.args
list of extra arguments to dist
cens.baseline
the baseline risk
cens.link
names of the link to the covariates
cens.max
maximal value where all event times are right censored
cens.type
"right" for right censored data, "interval" for interval
censored data
cens.coef
numeric vector of regression coefficients. the ith is
used for the ith entry of cova
cens.transform
list of function names one for each covariate,
where the ith element is applied
to values of the ith covariate before it is linked to generate the
survival times.
Possible distributions to generate covariates:
X.lognorm = list(dist = "rlnorm", meanlog = 2, sdlog = 0.4)
X.unif = list(dist = "runif", min = 0, max = 10),
X.exp = list(dist = "rexp", rate = 0.4)
X.bernoulli = list(dist = "rbinom", size = 1, prob = 0.3)
X.binom = list(dist = "rbinom", size = 4, prob = 0.8)
X.nbinom = list(dist = "rnbinom", size = 3, mu = 2)
X.poisson = list(dist = "rpois", lambda = 1.3)
A data.frame:
time |
the right censored event times |
status |
the survival status |
X |
the values of the covariate X |
f.X |
the transformed values of the covariate X |
time |
the uncensored event times |
Attributes of the data.frame
formula
a formula to evaluate the generated event history object
Thomas A. Gerds tag@biostat.ku.dk
Ralf Bender, Thomas Augustin, and Maria Blettner. Generating survival times to simulate Cox proportional hazards models by Ralf Bender, Thomas Augustin and Maria Blettner, Statistics in Medicine 2005; 24:1713-1723. Stat Med, 25(11):1978-9, 2006.
SimSurv(10) SurvData=SimSurv(100,cens.baseline=1/10,surv.baseline=2) Hist(SurvData$time,SurvData$status) prodlim(Hist(time,status)~1,data=SurvData) plot(prodlim(Hist(time,status)~1,data=SurvData)) plot(SurvData,atrisk=FALSE,legend=FALSE) SurvData=SimSurv(100,cens.baseline=1/10,surv.baseline=2,surv.coef=c(-1,-2), cova=list( X.exp = list(dist = "rexp", rate = 0.4), X.bernoulli = list(dist = "rbinom", size = 1, prob = 0.3))) SurvData=SimSurv(100,cens.baseline=1/10,surv.baseline=2,surv.coef=c(-1,-2),cens.coef=c(0,1), cova=list( X.exp = list(dist = "rexp", rate = 0.4), X.bernoulli = list(dist = "rbinom", size = 1, prob = 0.3))) ## Not run: coxph(Surv(time,status==0)~X.exp+X.bernoulli,data=SurvData) coxph(Surv(time,status)~X.exp+X.bernoulli,data=SurvData) ## End(Not run)