summary.jointSurroPenalSimul {frailtypack}

Short summary of the simulation studies based on a joint surrogate model

Description

This function returns the true value, the mean of the estimates, the empirical standard error, the mean of the estimated standard errors (Mean SE), and the coverage probability for model parameters

Usage

## S3 method for class 'jointSurroPenalSimul'
summary(object, d = 3, R2boot = 0, displayMSE = 0, printResult = 1, CP = 0,  ...)

Arguments

object

an object inheriting from jointSurroPenalSimul class.

d

The desired number of digits after the decimal point f. Default of 3

R2boot

A binary that specifies whether the confidence interval of R²_trial should be computed using parametric bootstrap (1) or Delta-method (0). The default is 0

displayMSE

A binary that indicates if the results include bias and mean square errors (MSE), case 1, or the standard errors with the coverage percentage, case 0. By default this argument is set to 0. In the event of 1 the results just include the individual level and the trial level association measurements.

printResult

A binary that indicates if the summary of the results should be displayed (1) or not (0). If this argument is set to 0, resuls are just returned to the user

CP

A binary that indicate in the event of displayMSE = 1 if the percentage of coverage should be display (1) or not (0). The default is 0

...

other unused arguments.

Value

For each parameter of the joint surrogate model , we print the true simulation value, the empirical standard error (empirical SE), the mean of the estimated standard errors (Mean SE), and the coverate probability (CP). For Kendall's \tau, the 95% Confidence interval is obtained by parametric bootstrap (for joint frailty model) or Delta-method (for joint frailty-copula model). For R²_trial(R2trial), the standard error is obtained by Delta-method and the 95% Confidence interval could be obtained directly or by parametric bootstrap. We also display the total number of non convergence case with the associated percentage (R : n(%)), the mean number of iterations to reach convergence, and other estimation and simulation parameters. We also return a dataframe of the simulations results .

Author(s)

Casimir Ledoux Sofeu [e-mail], [e-mail] and Virginie Rondeau [e-mail]

See Also

jointSurroPenalSimul

Examples

# Studies simulation
## Not run: 
# (Computation takes around 45 minutes using a processor including 40
# cores and a read only memory of 378 Go)
joint.simul <- jointSurroPenalSimul(nb.dataset = 10, nbSubSimul=600, 
                   ntrialSimul=30, LIMparam = 0.001, LIMlogl = 0.001, 
                   LIMderiv = 0.001, nb.mc = 200, nb.gh = 20, 
                   nb.gh2 = 32, true.init.val = 1, print.iter=F)

# results
summary(joint.simul, d = 3, R2boot = 1) # bootstrap
summary(joint.simul, d = 3, R2boot = 0) # Delta-method


## End(Not run)