Programs releases
Releases of programs for implementing modelling analyses.
Releases of programs for implementing modelling analyses.
Releases of subroutines used in modelling analyses.
We created a basic synthetic dataset of to represent a clinical youth mental health sample.
See how ready4 has been applied to real world decision problems.
Replication programs for designing, analysing and reporting discrete choice experiments.
Replication programs for constructing synthetic populations.
Replication programs for developing, finding and applying utility mapping algorithms.
Programs, sub-routines and user-interfaces combine ready4 modules and datasets to implement reproducible analyses of youth mental health policy and system design topics.
Decision aids provide user interfaces that make it easy to generate practical insight from ready4.
The code used when applying ready4 to a number of real world youth mental health policy and research projects is publicly available.
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.
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.
Applying Spring To Life model modules to map psychological and functional measures to AQoL-6D health utility
Applying the Springtides model to predict the potential mental health burden of COVID-19.
Initial set of academic posters relating to the development of the readyforwhatsnext model.