A collection of synthetic (fake) datasets to support the testing and illustration of algorithms developed for an AQoL-6D utility mapping study...
A results and replication dataset for an AQoL-6D utility mapping study. Contains model catalogues and model meta-data that can be used in conjunction with the youthu R package to predict AQoL-6D in clinical youth mental health samples...
**An** R subroutine program that authors a draft scientific manuscript for utility mapping studies documented with the TTU package...
**An** R package that includes tools to describe and quality assure types of data commonly present in youth mental health collections...
**An** R package that provides a framework, syntax and tools to support the development of open and modular mental health systems models...
**An** R program to replicate all steps from an AQoL-6D utility mapping study from original data ingest through analysis, reporting and results dissemination...
**An** R package that contains tools for creating model catalogues and scientific summaries for utility mapping studies and uploading study outputs to online repositories...
**An** R program to generate a synthetic (fake) dataset similar to that used to map a range of psychological measures to AQoL-6D health utility in a clinical sample of young people...
A key goal of scientific studies is that they are replicable, i.e. they can be repeated with different data. A step towards this goal is reproducibility, which means enabling other researchers to repeat a study using the same data. In principle, data synthesis and simulation studies have fewer potential barriers to reproducibility and replicability than many experimental designs as they are predominantly performed within scientific computing environments. However, in practice mental health projects of this type frequently have low levels of both reproducibility and replicability.