Finding modules and sub-modules
How to find individual ready4 modules and sub-modules.
How to find individual ready4 modules and sub-modules.
ready4 modules can be be used to model the people, places, platforms and programs that shape young people’s mental health.
To implement a modelling analysis with ready4 you need to install computational model modules.
Tools from the ready4class, ready4 fun and ready4pack R libraries streamline and standardise the authoring of ready4 modules.
Unreleased software and other preliminary work is currently being developed into modules for modelling people, places, platforms and programs.
A health economic model is a conceptual, mathematical and computational representation of systems relating to human health that can be used to help solve economic problems.
Some computational models are implemented by combining self-contained, reusable components called “modules”.
The ready4class R package supports partially automated and standardised workflows for defining the data structures to be used in computational models.
The ready4 software framework is currently being used to develop a modular economic model of youth mental health.
A ready4 computational model is implemented as a set of modules, all of which are authored with the ready4 software framework. These modules can be re-used and combined to create other computational models.
Replication programs for designing, analysing and reporting discrete choice experiments.
Costing health economic datasets is an activity that can involve repeated use of lookup tables. This tutorial describes how a module from the costly R package can help you to use a combination of fuzzy logic and correspondence tables to standardise variable values and thus facilitate partial automation of costing algorithms.
Modules to model the characteristics, relationships, behaviours, risk factors and outcomes of young people and individuals who interact with young people are collectively referred to as the “Spring To Life” model. The currently available modules listed here will be supplemented by additional unreleased work in progress.
This tutorial describes how a module from the costly R package can help you to use lookup codes to standardise variable values and thus facilitate partial automation of costing algorithms.
Appending appropriate metadata to datasets of individual unit records can facilitate partial automation of some modelling tasks. This tutorial describes how a module from the youthvars R package can help you to add metadata to a youth mental health dataset so that it can be more readily used by other ready4 modules.
Vector based classes can be used to help validate variable values. This tutorial describes how to do that with sub-module classes exported as part of the youthvars R package.
Modules for spatio-temporal modelling of the environments that shape young people’s mental health are collectively referred to as the “Springtides” model. Two module libraries are currently available - vicinity and aus, though both are highly preliminary and without any vignette articles to demonstrate their use. An app built using a combination of these libraries and unreleased work in progress module libraries is available for illustration purposes.
Using modules from the scorz R package, individual responses to a multi-attribute utility instrument survey can be converted into health utility total scores. This tutorial describes how to do for adolescent AQoL-6D health utility.
Modules that model the processes, eligibility requirements, staffing and configurations of youth service platforms are collectively referred to as the “First Bounce” model. No platforms modules are yet available - see details on unreleased work in progress.
Modules for modelling the efficacy, cost-effectiveness and budget impact of youth mental health programs (e.g. interventions for prevention, treatment and wellbeing) are collectively referred to as the “On Target” model. Some initial modules from the costly library are available. There is also even more preliminary work in progress.
Using modules from the specific R package, it is possible to undertake an exploratory utility mapping analysis. This tutorial illustrates a hypotehtical example of exploring how to map to EQ-5D health utility.
Using modules from the TTU R package, it is possible to implement a fully reproducible utility mapping study. This tutorial illustrates the main steps using a hypothetical AQoL-6D utility mapping study.
Using tools (soon to be formalised into ready4 modules) from the youthu R package, it is possible to find and deploy relevant utility mapping algorithms. This tutorial illustrates the main steps for predicting AQoL-6D utility from psychological and functional measures collected on clinical samples of young people.
We used functions (soon to be formalised into ready4 modules) from the mychoice R package to design to a discrete choice experiment.
Using tools (soon to be formalised into ready4 framework modules) from the youthu R package, it is possible to use utility mapping algorithms to help implement cost-utility analyses. This tutorial illustrates the main steps for doing so using psychological and functional measures collected on clinical samples of young people.
Using tools (soon to be formalised into ready4 framework modules) from the mychoice R package, it is possible to develop choice models from responses to a discrete choice experiment survey.
Using functions (soon to be formalised into ready4 framework modules) from the mychoice R package, it is possible to develop choice models from responses to a discrete choice experiment survey.
We previously developed a user interface for the epidemiology modules of our Springtides model of places.
Using modules from the TTU, youthvars, scorz and specific libraries, we developed utility mapping algorithms from a sample of young people attending primary mental health care services.
Using functions (soon to be formalised into ready4 framework modules) from the youthu R package, we predicted health utility for a synthetic population of young people attending primary mental health care services.
Current unreleased work to develop modules for modelling the characteristics, relationships, behaviours, risk factors and outcomes of young people and those important to them.
Current unreleased work to develop modules for modelling the demographic, environmental and proximity drivers of access, equity and outcomes in youth mental health.
Current unreleased work to develop modules for modelling the optimal staffing and configuration of support services for young people.
Current very preliminary work to develop modules for modelling the affordability, value for money and appropriate targeting of interventions for young people.
A subroutine for generating catalogues of utility mapping models created with the TTU library.
A subroutine for generating a scientific manuscript of a longitudinal utility mapping study undertaken with the TTU library.
A subroutine for a summary of the main results from a Discrete Choice Experiment implemented with the mychoice library.
The ready4 framework is introduced in an article from the PharmacoEconomics journal.
Announcing the first CRAN release of the ready4 library.
Announcing the introduction of a novel approach to developing modular models with a simple, consistent syntax.