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 |
| Nutritional Epidemiology | About Food |
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Study design
- Survey
- Clinical trial design
- Phase I, II, III
- adaptive design
- Sample size calculation
- comparing a few groups (visualization TBD)
- regression (LR, GLM)
- more advanced model (e.g. GLMM)
| Title | Description |
|---|---|
| Clinical trial design: overview | Notes related to clinical trial design. |
| Sample size (part I) | Overview, mean and proportion comparison |
| Sample size (part II) | Regression |
| Adaptive design: overview | Intro to adaptive design |
| Survey, stratification | Survey sampling |
| Study design and statistical inference | Terminology and examples |
| Observational study design | Cohort, case control and related metrics |
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Causal inference
| Title | Description |
|---|---|
| Overview: causal inference | Collider, confounder, mediator and M-bias |
| General techniques | (to be integrated) |
| G-Computation | G-Computation |
| Notes from book: What If (Part 1) | Causal inference notes: chapter 1 to 10 |
| Notes from book: What if (Part 2) | IP weighting, standardization (g-computation) |
| Notes from book: What if (Part 3) | Outcome regression, propensity score |
| Notes from book: What if (Part x) | Instrumental variables |
| Matching | Overview of matching techniques |
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Models
| Title | Description |
|---|---|
| Regression | Linear, logistic, Cox proportional hazard |
| Mixed models for repeted measurements | Resources: |
| Survival | Links |
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Other topics
Topics on inference in general, missing value handling
| Title | Description |
|---|---|
| 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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Case studies
| Title | Description |
|---|---|
| Length of hospital stay: Part I | Part 1: EDA |
| Length of hospital stay: Part II | Part 2: time-to-event analysis |
| Linear regression example: prestige | Linear regression |
| Logistic regression example: lung | Logistic regression |
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Interview preparation
| Title | Description |
|---|---|
| Interview: clinical trial statistician | Knowledge framework |
| Interview: behavior | List of questions |
| Interview: statistics used in my work | Case studies |
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