Posts tagged workflow
The Bayesian Workflow: COVID-19 Outbreak Modeling
- 16 June 2025
Bayesian modeling is a robust approach for drawing conclusions from data. Successful modeling involves an interplay among statistical models, subject matter knowledge, and computational techniques. In building Bayesian models, it is easy to get carried away with complex models from the outset, often leading to an unsatisfactory final result (or a dead end). To avoid common model development pitfalls, a structured approach is helpful. The Bayesian workflow (Gelman et al.) is a systematic approach to building, validating, and refining probabilistic models, ensuring that the models are robust, interpretable, and useful for decision-making. The workflow’s iterative nature ensures that modeling assumptions are tested and refined as the model grows, leading to more reliable results.