MAEQJMMLSM | R Documentation |
A metric of prediction accuracy of joint model by comparing the predicted risk with the empirical risks stratified on different predicted risk group.
MAEQJMMLSM(
seed = 100,
object,
landmark.time = NULL,
horizon.time = NULL,
obs.time = NULL,
method = c("Laplace", "GH"),
quadpoint = NULL,
maxiter = 1000,
survinitial = TRUE,
n.cv = 3,
quantile.width = 0.25,
opt = "nlminb",
initial.para = FALSE,
...
)
seed |
a numeric value of seed to be specified for cross validation. |
object |
object of class 'JMMLSM'. |
landmark.time |
a numeric value of time for which dynamic prediction starts.. |
horizon.time |
a numeric vector of future times for which predicted probabilities are to be computed. |
obs.time |
a character string of specifying a longitudinal time variable. |
method |
estimation method for predicted probabilities. If |
quadpoint |
the number of standard Gauss-Hermite quadrature points if |
maxiter |
the maximum number of iterations of the EM algorithm that the function will perform. Default is 10000. |
survinitial |
Fit a Cox model to obtain initial values of the parameter estimates. Default is TRUE. |
n.cv |
number of folds for cross validation. Default is 3. |
quantile.width |
a numeric value of width of quantile to be specified. Default is 0.25. |
opt |
Optimization method to fit a linear mixed effects model, either nlminb (default) or optim. |
initial.para |
Initial guess of parameters for cross validation. Default is FALSE. |
... |
Further arguments passed to or from other methods. |
a list of matrices with conditional probabilities for subjects.
Shanpeng Li lishanpeng0913@ucla.edu
JMMLSM, survfitJMMLSM
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