Browse by topic, not just chronology
The archive is finally big enough that a date-sorted list is lazy navigation. These topic pages group related guides so readers can stay inside one problem family, whether they care about identification, bias diagnostics, or study design.
AI-Assisted Research
Latest: Data Leakage in Clinical Prediction Models: When the Model Learns the Future
Bias Diagnostics
Latest: Channeling Bias: When the Newer Treatment Inherits the Easier Patients
Biomarkers
Latest: Surrogate Endpoints: When a Biomarker Improvement Pretends to Be Patient Benefit
Case-Crossover Design
Latest: Case-Crossover Design: When Patients Become Their Own Controls
Causal Framework
Latest: Structural Causal Models & DAGs: A Practical Guide for Clinical Researchers
Causal Inference
Latest: Treatment-Induced Mediator-Outcome Confounding: When Mediation Analysis Starts Chasing the Consequences of Treatment
Clinical AI
Latest: Prediction vs Causation: Why Your Best Risk Model Still Cannot Tell You What to Treat
Clinical Epidemiology
Latest: Healthy Adherer Bias: When Persistence Looks Like Pharmacology
Clinical Outcomes
Latest: Competing Risks: When Kaplan-Meier Tells the Wrong Clinical Story
Clinical Trials
Latest: Adaptive Enrichment Trials: When Precision for One Subgroup Pretends to Be Evidence for Everyone
Clinical Utility
Latest: Net Reclassification Improvement: When a New Biomarker Wins by Moving Patients Between the Wrong Boxes
Collider Bias
Latest: Collider Bias: How Adjustment Can Manufacture Associations
Confounding by Indication
Latest: Confounding by Indication: When Sicker Patients Make Treatments Look Dangerous
DAGs
Latest: Overadjustment Bias: When More Covariates Make Causal Inference Worse
DID
Latest: Difference-in-Differences: A Practical Guide for Clinical Researchers
Effect Measures
Latest: Noncollapsibility of Odds Ratios: Why Adjustment Can Change the Number Even When Confounding Did Not
Estimands
Latest: When Death Changes the Question: Competing Risks, Intercurrent Events, and Truncation by Death
External Validity
Latest: Transportability & External Validity: When Your Causal Estimate Travels, and When It Absolutely Does Not
G-Computation
Latest: G-Computation: Predict the Outcome Under Each Treatment Strategy
G-Estimation
Latest: G-Estimation: The Causal Method You Reach For When Time-Varying Confounding Breaks Regression
G-Formula
Latest: Parametric G-Formula: Estimating Causal Effects When Covariates Change Over Time
Genetic Epidemiology
Latest: Mendelian Randomization: Using Genetics as Nature's Randomized Trial
Heterogeneous Effects
Latest: Causal Forests: Finding Treatment Effect Heterogeneity Without Fooling Yourself
High-Dimensional Data
Latest: Double Machine Learning: A Practical Guide for Clinical Researchers
IPW
Latest: Inverse Probability Weighting: When PSM Discards Your Data
Identification
Latest: Front-Door Criterion: The Causal Backdoor Alternative Nobody Uses Enough
Immortal Time Bias
Latest: Immortal Time Bias: The Fake Survival Advantage Hiding in Bad Study Design
Instrumental Variables
Latest: Instrumental Variables: When Observational Data Meets Unmeasured Confounding
Interference
Latest: Interference & Spillover Effects: When One Patient's Treatment Changes Another's Outcome
Interrupted Time Series
Latest: Interrupted Time Series: Strong Quasi-Experiments Need More Than a Before-and-After Plot
Landmark Analysis
Latest: Landmark Analysis: Useful, Honest, and Frequently Overclaimed
Longitudinal Data
Latest: Time-Varying Confounding: When Yesterday's Treatment Changes Today's Confounder
MSM
Latest: Marginal Structural Models: A Practical Guide for Clinical Researchers
Machine Learning
Latest: Targeted Maximum Likelihood Estimation: Doubly Robust, Not Doubly Forgiving
Measurement Error
Latest: Differential Misclassification: When One Study Arm Gets More Chances to Be Wrong
Mechanisms
Latest: Mediation Analysis: When You Want the Mechanism, Not Just the Effect
Mediation Analysis
Latest: Treatment-Induced Mediator-Outcome Confounding: When Mediation Analysis Starts Chasing the Consequences of Treatment
Mendelian Randomization
Latest: Mendelian Randomization: Using Genetics as Nature's Randomized Trial
Methods Critique
Latest: Differential Misclassification: When One Study Arm Gets More Chances to Be Wrong
Missing Data
Latest: Jump-to-Reference Imputation: When Missing Outcomes Start Borrowing the Control Arm's Future
Observational Studies
Latest: Bias Amplification: When Adjustment Makes Unmeasured Confounding Worse
Oncology
Latest: Treatment Switching in Oncology Trials: When Overall Survival Becomes a Rescue Protocol Audit
Outcome Measurement
Latest: Differential Misclassification: When One Study Arm Gets More Chances to Be Wrong
PSM
Latest: Propensity Score Matching: A Practical Guide for Clinical Researchers
Pharmacoepidemiology
Latest: Washout Periods: When “New Use” Is Just Old Use with Better PR
Policy Evaluation
Latest: Stochastic Interventions: When “Treat Everyone” Is Not the Policy Question
Positivity
Latest: Positivity & Overlap: The Assumption Your Causal Estimate Cannot Survive Without
Prediction Models
Latest: Data Leakage in Clinical Prediction Models: When the Model Learns the Future
Principal Stratification
Latest: Principal Stratification: Estimating Effects When Post-Treatment Variables Matter
Propensity Scores
Latest: Positivity & Overlap: The Assumption Your Causal Estimate Cannot Survive Without
Quasi-Experimental
Latest: Regression Discontinuity Design: A Practical Guide for Clinical Researchers
RDD
Latest: Regression Discontinuity Design: A Practical Guide for Clinical Researchers
RMST
Latest: Restricted Mean Survival Time: When Hazard Ratios Are Not the Clinical Answer
Real-World Evidence
Latest: Channeling Bias: When the Newer Treatment Inherits the Easier Patients
Reporting Bias
Latest: Outcome Switching: When the Primary Endpoint Moves After the Results Get Interesting
Screening Studies
Latest: Overdiagnosis: When Finding More Disease Does Not Mean Saving More Lives
Selection Bias
Latest: Selection Bias: When Your Study Sample Is the Problem
Self-Controlled Designs
Latest: Self-Controlled Case Series: When Each Patient Becomes Their Own Control
Sensitivity Analysis
Latest: MNAR Sensitivity Analysis: Because “We Assumed MAR” Is Not a Results Section
Standardization
Latest: G-Computation: Predict the Outcome Under Each Treatment Strategy
Study Design
Latest: AI-Assisted Methods Review: What LLMs Can Catch, What They Cannot, and Where Judgment Still Matters
Survival Analysis
Latest: When Death Changes the Question: Competing Risks, Intercurrent Events, and Truncation by Death
Synthetic Control
Latest: Synthetic Control Methods: Building Counterfactuals When DID Fails
TMLE
Latest: Targeted Maximum Likelihood Estimation: Doubly Robust, Not Doubly Forgiving
Target Trial Emulation
Latest: Time Zero Alignment: When Your Cohort Starts Counting Before Treatment Does
Time-Varying Confounding
Latest: Time-Varying Confounding: When Yesterday's Treatment Changes Today's Confounder
Trial Design
Latest: Adaptive Enrichment Trials: When Precision for One Subgroup Pretends to Be Evidence for Everyone
Trial Interpretation
Latest: Principal Stratification: Estimating Effects When Post-Treatment Variables Matter
Unmeasured Confounding
Latest: Proximal Causal Inference: What to Do When Unmeasured Confounding Is Still on the Table
Need the full archive instead?
If you already know the method name, the main blog explorer is still the fastest route.