Author And Document Modules Of Health Economic ModelsSource:
The ready4 framework uses object oriented programming (OOP) to implement modular approaches to computational models of mental health systems. That means that a standardised approach to developing modules (S4 classes) and sub-modules (S3 classes) is required. ready4class provides the tools to implement this workflow.
The main classes exported as part of
a tibble based ready4
sub-module, which contains metadata on the prototypes of classes
that can be used as sub-components of ready4 modules and sub-modules
(for example a tibble based class can be used as a slot in an S4 class).
When authoring ready4 R packages, you will create a
ready4class_pt_lup instance and store it in an online
repository that you have write permissions to. As you create new ready4
modules and sub-modules using
ready4class tools, your
ready4class_pt_lup object will be updated so that these
classes can be made available to any future modules or sub-modules that
you author. The
ready4class_pt_lup sub-module recently used
in workflows for authoring ready4 modules is reproduced below.
x <- ready4use::Ready4useRepos(gh_repo_1L_chr = "ready4-dev/ready4",
gh_tag_1L_chr = "Documentation_0.0") %>%
ingest(fls_to_ingest_chr = "prototype_lup",
metadata_1L_lgl = F)
exhibit(scroll_box_args_ls = list(width = "100%"))
ready4class_constructor is another tibble based ready4
sub-module that summarises the desired features of the ready4 modules
and sub-modules that you are authoring. An instance of
ready4class_constructor is combined with a
sub-module to create a
ready4class_constructor are most efficiently
created using the
The most important method included in
ready4class is the
author method for the
sub-module, that enhances the
author method defined for the
ready4fun_manifest so that consistently documented R
package classes are also generated.
## Not run
ready4class sub-modules and methods are not intended for
independent use, but instead should be deployed as part of ready4pack
R package authoring workflow.
It should be noted that some
ready4class methods require
files of a standardised format to be saved in specific sub-directories
of the package
data-raw directory. Detailed instructions on
how to prepare these files are not yet available, but will be outlined
in documentation to be released in 2022.