projects:workgroups:patient-level_prediction:best-practice
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Table of Contents
OHDSI Best Practices for Patient Level Prediction Modelling
This document is under development. Changes can be proposed and discussed via the OHDSI Forum and in the Population-Level Estimation Workgroup meetings.
General principles
- Transparency: others should be able to reproduce your study in every detail using the information you provide.
- Prespecify what you're going to estimate and how: this will avoid hidden multiple testing (fishing expeditions, p-value hacking). Run your analysis only once.
- Validation of your analysis: you should have evidence that your analysis does what you say it does (showing that statistics that are produced have nominal operating characteristics (e.g. p-value calibration), showing that specific important assumptions are met (e.g. covariate balance), using unit tests to validate pieces of code, etc.)
Best practices (generic)
projects/workgroups/patient-level_prediction/best-practice.1461088153.txt.gz · Last modified: by prijnbeek
