A generic function for creating an object of class IndivCtstmTrans
.
create_IndivCtstmTrans(object, ...) # S3 method for flexsurvreg_list create_IndivCtstmTrans( object, input_data, trans_mat, clock = c("reset", "forward"), n = 1000, uncertainty = c("normal", "none"), ... ) # S3 method for flexsurvreg create_IndivCtstmTrans( object, input_data, trans_mat, clock = c("reset", "forward"), n = 1000, uncertainty = c("normal", "none"), ... ) # S3 method for params_surv create_IndivCtstmTrans( object, input_data, trans_mat, clock = c("reset", "forward", "mix"), reset_states = NULL, ... ) # S3 method for params_surv_list create_IndivCtstmTrans( object, input_data, trans_mat, clock = c("reset", "forward", "mix"), reset_states = NULL, ... )
object  An object of the appropriate class containing either a fitted multistate model or parameters of a multistate model. 

...  Further arguments passed to 
input_data  An object of class 
trans_mat  The transition matrix describing the states and transitions in a
multistate model in the format from the 
clock  "reset" for a clockreset model, "forward" for a clockforward model, and "mix" for a mixture
of clockreset and clockforward models. See the field 
n  Number of random observations to draw. Not used if 
uncertainty  Method determining how parameter uncertainty should be handled.
If 
reset_states  A vector denoting the states in which time resets. See the field

Returns an R6Class
object of class IndivCtstmTrans
.
Disease models may either be created from a fitted statistical
model or from a parameter object. In the case of the former, input_data
is a data frame like object that is used to look for variables from
the statistical model that are required for simulation. In this sense,
input_data
is very similar to the newdata
argument in most predict()
methods (e.g., see predict.lm()
). In other words, variables used in the
formula
of the statistical model must also be in input_data
.
In the case of the latter, the columns of input_data
must be named in a
manner that is consistent with the parameter object. In the typical case
(e.g., with params_surv
or params_mlogit
), the parameter object
contains coefficients from a regression model, usually stored as matrix
where rows index parameter samples (i.e., for a probabilistic sensitivity
analysis) and columns index model terms. In such instances, there must
be one column from input_data
with the same name as each model term in the
coefficient matrix; that is, the columns in input_data
are matched with
the columns of the coefficient matrices by name. If there are model terms
in the coefficient matrices that are not contained in input_data
, then
an error will be thrown.
See IndivCtstmTrans
and IndivCtstm
for examples.