Epidemiology: Study Designs — Advanced Methodology and Biostatistics

Public Health and Epidemiology · Clinical Bases

How it begins

An exhaustive and mathematically rigorous analysis of the methodological architecture in epidemiological research. From the descriptive report to the randomized clinical trial and Mendelian randomization models.

What it covers

1. Fundamentals of Methodology and Causal Inference
2. · 1.1 Historical Evolution of Research Designs
3. · 1.2 Causal Models: Triad, Rothman and Bradford Hill Criteria
4. · 1.3 Methodological Axes of Classification
5. Descriptive and Ecological Studies
6. · 2.1 Reports and Clinical Case Series
7. · 2.2 Ecological or Correlation Studies
8. · 2.3 The Phenomenon of the Ecological Fallacy
9. Cross-Sectional Studies
10. · 3.1 Methodological Architecture and Sampling Strategies
11. · 3.2 Measures of Association: Prevalence Ratio (PR) and Prevalence Odds Ratio (by)
12. · 3.3 Neyman Bias (Prevalence-Incidence), Length and Temporal Ambiguity
13. Case and Control Studies
14. · 4.1 Methodological Selection of Cases and Controls
15. · 4.2 The Matching Process and the Overlap Phenomenon
16. · 4.3 Mathematical Demonstration of the Odds Ratio as an Estimator of Relative Risk
17. · 4.4 Advanced Methodological Variants
18. Cohort Studies
19. · 5.1 Temporal Taxonomy of Cohorts
20. · 5.2 Frequency Quantification: Cumulative Incidence and Incidence Rate
21. · 5.3 Association Measures and Population Impact
22. · 5.4 The Challenge of Tracking Losses (Attrition Bias)
23. Randomized Clinical Trials
24. · 6.1 Randomization and Masking Methodology
25. · 6.2 Design Variations: Parallel, Crossover and Factorial
26. · 6.3 Analysis Paradigms: Intention to Treat (ITT) versus Per Protocol (PP)
27. · 6.4 Ethics and Integrity in Clinical Research
28. Quasi-Experimental Designs
29. · 7.1 Analysis of Interrupted Time Series (ITS)
30. · 7.2 Regression Discontinuity Design (RDD)
31. · 7.3 Difference in Differences (DiD) Methodology
32. Modern and Advanced Epidemiological Designs
33. · 8.1 Mendelian Randomization
34. · 8.2 Real Life Evidence (RWE) and Real Life Data (RWD)
35. Systematic Reviews and Meta-Analysis
36. · 9.1 PRISMA Search and Declaration Methodology
37. · 9.2 Mathematical Models: Fixed Effects vs. Random Effects
38. · 9.3 Evaluation and Quantification of Heterogeneity
39. · 9.4 Publication Bias: Funnel Plot, Egger Test and Trim-and-Fill
40. · 9.5 Network Meta-Analysis
41. Systematic Errors, Confusion and Interaction
42. · 10.1 Taxonomy of Biases in Epidemiology
43. · 10.2 Control of Confounding Variables
44. · 10.3 Biological Interaction and Effect Modification
45. Reporting and Scientific Rigor Guides