Installing tools for authoring computational models
Instructions for installing the ready4class, ready4fun and ready4pack libraries.
Tag: Status - development
Template module
ready4 provides a template to facilitate modular implementation of health economic models.
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Installing tools for authoring and managing model datasets
Instructions for installing the ready4use library.
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Provide end users with a simple and consistent syntax for using model modules
Methods are associated with ready4 modules using a novel syntax.
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Installing tools for authoring reproducible analyses
Instructions for installing the ready4show library.
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Create a synthetic population of young people attending primary mental health services
We created a basic synthetic dataset of to represent a clinical youth mental health sample.
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Partially automate maintenance of a modelling project's website
ready4 includes tools that can help maintain the documentation website for a modelling project.
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Why ready4 is object oriented
ready4 uses an object oriented programming (OOP) paradigm to implement computational models.
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Authoring model data structures
The ready4class R package supports partially automated and standardised workflows for defining the data structures to be used in computational models.
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The role of functional programming in ready4 development
ready4 uses functional programming to maximise the re-usability of model algorithms.
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Authoring model algorithms
The ready4fun R package supports standardised approaches to code authoring that facilitate partial automation of the documenting of model algorithms.
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Dissemating citable, documented and quality assured model module libraries
ready4 supports tools to streamline the testing, description and distribution of computational model modules.
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Find themed collections of ready4 modules
Tools from the ready4 R library can help find details about module libraries from a modelling project.
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Commands for using model modules
Apply model modules using a simple and consistent syntax.
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Ingest data from an open access repository
A tutorial from the Acumen website about using ready4 to search and retrieve data from the Australian Mental Health Systems Models Dataverse.
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Search open access data collections
Online open access data repositories are the preferred storage locations for ready4 model datasets.
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Standardise Variable Values With Fuzzy Logic And Correspondence Tables
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.
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Finding modules of health economic models
The ready4 library provides tools to help retrieve details of model module collections and documentation on individual model modules.
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Find examples of how model modules are used
Tools from the ready4 R library can help find details about the use of individual model modules.
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Authoring scientific manuscripts
Tools from the ready4show R package support authoring of scientific summaries of analyses with ready4.
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Add a data dictionary to a dataset
Pairing a dataset with its dictionary makes it easier to interpret. This tutorial describes how a module from the ready4use R package can help you to pair a dataset and its dictionary.
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Standardise Variable Values With Lookup Codes
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.
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Add metadata to datasets of individual human records
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.
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Validate variable total scores
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.
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Ingest, label and share model data
The ready4use R package provides tools for supplying data to model modules.
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Using model modules for repeatable analyses
The ready4 framework provides tools to support the authoring of programs and subroutines to run and report analyses with ready4.
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Share data via online repositories
The retrieval and dissemination of data from online data repositories is an essential enabler of open source modelling. This tutorial describes how a module from the ready4use R package can help you to manage this process.
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Score health utility
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.
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Explore candidate utility mapping models
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.
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Implement a utility mapping study
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.
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Find and deploy utility mapping models
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.
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Design a Discrete Choice Experiment
We used functions (soon to be formalised into ready4 modules) from the mychoice R package to design to a discrete choice experiment.
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Use utility mapping algorithms to help implement cost-utility analyses
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.
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Develop choice models
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.
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Analyse the results of a Discrete Choice Experiment
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.
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Develop health utility mapping algorithms
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.
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Predict health utility
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.
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Framework library descriptions
There are two types of framework libraries - a foundational library and libraries of authoring tools.
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Pipeline of programs modules
Current very preliminary work to develop modules for modelling the affordability, value for money and appropriate targeting of interventions for young people.
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Make a catalogue of utility mapping models
A subroutine for generating catalogues of utility mapping models created with the TTU library.
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Author a template scientific manuscript
A template subroutine for generating a scientific manuscript for use with the ready4show library.
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Author a draft scientific manuscript for a utility mapping study
A subroutine for generating a scientific manuscript of a longitudinal utility mapping study undertaken with the TTU library.
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Make results summary for a Discrete Choice Experiment
A subroutine for a summary of the main results from a Discrete Choice Experiment implemented with the mychoice library.
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Development releases
Development releases provide the most comprehensive and up to date public record of a ready4 project’s source code but may be poorly documented and tested.