Description Usage Arguments Details Value Author(s) References See Also Examples
View source: R/jointSurrSimul.R
Date are generated from the onestep joint surrogate model (see jointSurroPenal
for more details)
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32  jointSurrSimul(
n.obs = 600,
n.trial = 30,
cens.adm = 549.24,
alpha = 1.5,
theta = 3.5,
gamma = 2.5,
zeta = 1,
sigma.s = 0.7,
sigma.t = 0.7,
cor = 0.8,
betas = 1.25,
betat = 1.25,
frailt.base = 1,
lambda.S = 1.8,
nu.S = 0.0045,
lambda.T = 3,
nu.T = 0.0025,
ver = 1,
typeOf = 1,
equi.subj.trial = 1,
equi.subj.trt = 1,
prop.subj.trial = NULL,
prop.subj.trt = NULL,
full.data = 0,
random.generator = 1,
random = 0,
random.nb.sim = 0,
seed = 0,
nb.reject.data = 0,
pfs = 0
)

n.obs 
Number of considered subjects. The default is 
n.trial 
Number of considered trials. The default is 
cens.adm 
censorship time. The default is 
alpha 
Fixed value for α. The default is 
theta 
Fixed value for θ. The default is 
gamma 
Fixed value for γ. The default is 
zeta 
Fixed value for ζ. The default is 
sigma.s 
Fixed value for
σ^{2}_{vS}.
The default is 
sigma.t 
Fixed value for
σ^{2}_{vT}.
The default is 
cor 
Desired level of correlation between v_{Si} and v_{Ti}.

betas 
Fixed value for β_{S}.
The default is 
betat 
Fixed value for β_{T}.
The default is 
frailt.base 
considered the heterogeneity on the baseline risk 
lambda.S 
Desired scale parameter for the 
nu.S 
Desired shape parameter for the 
lambda.T 
Desired scale parameter for the 
nu.T 
Desired shape parameter for the 
ver 
Number of covariates. For surrogte evaluation, we just considered one covatiate, the treatment arm 
typeOf 
Type of joint model used for data generation: 0 = classical joint model
with a shared individual frailty effect (Rondeau, 2007), 1 = joint surrogate model with shared frailty
effects 
equi.subj.trial 
A binary variable that indicates if the same proportion of subjects should be included per trial (1)
or not (0). If 0, the proportions of subject per trial are required in parameter 
equi.subj.trt 
A binary variable that indicates if the same proportion of subjects is randomized per trial (1)
or not (0). If 0, the proportions of subject per trial are required in parameter 
prop.subj.trial 
The proportions of subjects per trial. Requires if 
prop.subj.trt 
The proportions of randomized subject per trial. Requires if 
full.data 
Specified if you want the function to return the full dataset (1), including the random effects,
or the restictive dataset (0) with 
random.generator 
Random number generator used by the Fortran compiler,

random 
A binary that says if we reset the random number generation with a different environment
at each call 
random.nb.sim 
required if 
seed 
The seed to use for data (or samples) generation. Required if the argument 
nb.reject.data 
Number of generation to reject before the considered dataset. This parameter is required
when data generation is for simulation. With a fixed parameter and 
pfs 
Is used to specify if the time to progression should be censored by the death time (0) or not (1). The default is 0. In the event with pfs set to 1, death is included in the surrogate endpoint as in the definition of PFS or DFS. 
We just considered in this generation, the Gaussian random effects. If the parameter full.data
is set to 1,
this function return a list containning severals parameters, including the generated random effects.
the desired individual level correlation (Kendall's τ) depend on the values of
α, θ, γ and ζ.
This function return if the parameter full.data
is set to 0, a data.frame
with columns :
patientID 
A numeric, that represents the patient's identifier, must be unique; 
trialID 
A numeric, that represents the trial in which each patient was randomized; 
trt 
The treatment indicator for each patient, with 1 = treated, 0 = untreated; 
timeS 
The follow up time associated with the surrogate endpoint; 
statusS 
The event indicator associated with the surrogate endpoint. Normally 0 = no event, 1 = event; 
timeT 
The follow up time associated with the true endpoint; 
statusT 
The event indicator associated with the true endpoint. Normally 0 = no event, 1 = event; 
If the argument full.data
is set to 1, additionnal colums corresponding to random effects
ω_{ij},
u
_{i}, v_{Si} and
v_{Ti} are returned. Note that
u
_{i}, v_{Si} and
v_{Ti} are returned if typeOf
is set to 1
Casimir Ledoux Sofeu casimir.sofeu@ubordeaux.fr, scl.ledoux@gmail.com and Virginie Rondeau virginie.rondeau@inserm.fr
Rondeau V., MathoulinPelissier S., JacqminGadda H., Brouste V. and Soubeyran P. (2007). Joint frailty models for recurring events and death using maximum penalized likelihood estimation: application on cancer events. Biostatistics 8(4), 708721.
Sofeu, C. L., Emura, T., and Rondeau, V. (2019). Onestep validation method for surrogate endpoints using data from multiple randomized cancer clinical trials with failuretime endpoints. Statistics in Medicine 38, 29282942.
1 2 3 4 5 6 7 8  ## Not run:
data.sim < jointSurrSimul(n.obs=600, n.trial = 30,cens.adm=549.24,
alpha = 1.5, theta = 3.5, gamma = 2.5, sigma.s = 0.7,
zeta = 1, sigma.t = 0.7, cor = 0.8, betas = 1.25,
betat = 1.25, full.data = 0, random.generator = 1,
seed = 0, nb.reject.data = 0, pfs = 0)
## End(Not run)

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