Optimize your analytical validation studies for novel digital clinical measures

As a statistician, your sDHT developer colleagues likely consult you to help design analytical validation studies and statistical analysis plans.

Although many statistical methods are well established, knowing which one to choose depending on study parameters, such as the intended context of use, the rigor of available reference measures, and whether or not the digital clinical measure is novel, remains a challenge.

These resources will help you optimize your analytical validation study by establishing a shared framework on reference measure rigor, including in-depth resources to evaluate new approaches to conduct a comparative analysis when the units of your digital clinical measure of interest and reference measure are not directly comparable.

Biostatistician

Support your colleagues in developing statistically sound analytical validation studies and access a simulation toolkit to quickly game out more complex reference measure comparisons

Resources designed for Biostatisticians

Interactive Guide to Validating Novel Digital Clinical Measures

The interactive guide provides a high-level decision process for designing an analytical validation study. It introduces a structured framework to select fit-for-purpose reference measures.

USE THIS RESOURCE

The Simulation Toolkit for Digital Clinical Measure Analytical Validation

Use the toolkit when your measure of interest and reference measure do not have directly comparable units. It bundles methods for data simulation and an approach to design comparative studies.

You can find additional information on applicable statistical methods in this document.

USE THIS RESOURCE