Inference and models
Settings
Different settings to apply methods.
| Title | Description |
|---|---|
| Real-world Data, Real-world Evidence | RWD, RWE |
| Genomics in Drug Discovery | Use of machine learning techniques |
| Antibiotics | Background of antimicrobial drugs and resistance |
| RWD EHR Vendor Engagement | Overview of vendor engagement |
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Inference
Notes on causal inference and other related topics.
| Title | Description |
|---|---|
| Overview: causal inference | Collider, confounder, mediator and M-bias |
| Weighting | Propensity score, matching, weighting |
| Target trial emulation | TTE |
| G-Computation | G-Computation |
| Missing data and imputation | Overview of multiple imputation |
| Multiple imputation in R |
MICE, regression, PMM
|
| Intervals | Confidence, credible and prediction intervals |
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Models
| Title | Description |
|---|---|
| Mixed models for repeted measurements | Resources: |
| Survival | Links |
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Case studies
| Title | Description |
|---|---|
| Case study: length of hospital stay | Part 1: EDA |
| Case study: CTN | Data challenge R/Medicine 2024 |
| Case study: CTN-51 | Focusing on CTN 51 data |
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