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.
Tag: Analyses - replication code
Examples
See how ready4 has been applied to model real world decision problems.
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Model youth choices
Replication programs for designing, analysing and reporting discrete choice experiments.
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Create synthetic populations
Replication programs for constructing synthetic populations.
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Model health utility
Replication programs for developing, finding and applying utility mapping algorithms.
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Code to reproduce and/or replicate scientific studies
The code used when applying ready4 to a number of real world youth mental health policy and research projects is publicly available.
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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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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.