A list of resources related to health data science, population health and clinical data science.
- Bayes Rules! An Introduction to Applied Bayesian Modeling
- Statistical Tools for Causal Inference
- The Epidemiologist R Handbook
- Machine Learning-based Causal Inference Tutorial
- Biostatistics reading list by Justin Belair, covering topics such as:
- Hypothesis Testing
- Misinterpretations of p-values, power analysis, and other concepts
- Design of Experiments
- Lord's Paradox
- Philosophical Questions
- Classics
- Missing Data
- Causal Inference
- Epidemiology
- Bradford Hill Criteria And Their Legacy
- Time-series Models
- Modeling ordinal data
- Modeling proportions data (in the 0-1 interval)
- Attention is all you need
- Open AI's paper: Training Language Models to Follow Instructions with Human Feedback
- Summary here