Methods Critique
Everything on Aqrab tagged Methods Critique — grouped into one landing page so readers can go deeper by problem family instead of bouncing around the archive blind.
Differential Misclassification: When One Study Arm Gets More Chances to Be Wrong
A practical guide to differential misclassification for clinical researchers. Covers arm-specific outcome detection, adjudication asymmetry, false positives, missed events, and what reviewers should demand before trusting an effect estimate.
Adaptive Enrichment Trials: When Precision for One Subgroup Pretends to Be Evidence for Everyone
A practical guide to adaptive enrichment trials for clinical researchers. Covers predictive versus prognostic enrichment, assay timing, multiplicity, external validity, and what reviewers should demand before trusting a biomarker-selected win.
Treatment-Induced Mediator-Outcome Confounding: When Mediation Analysis Starts Chasing the Consequences of Treatment
A practical guide to treatment-induced mediator-outcome confounding for clinical researchers. Covers why natural direct and indirect effects fail when treatment changes later severity, toxicity, adherence, or surveillance that affect both the mediator and outcome.
Surrogate Endpoints: When a Biomarker Improvement Pretends to Be Patient Benefit
A practical guide to surrogate endpoints for clinical researchers. Covers validated versus merely plausible surrogates, classic failure modes, and what reviewers should demand before trusting a biomarker-driven trial claim.
Data Leakage in Clinical Prediction Models: When the Model Learns the Future
A practical guide to data leakage in clinical prediction models for clinical researchers. Covers post-outcome features, workflow proxies, validation traps, and what reviewers should demand before trusting a headline AUC.
Net Reclassification Improvement: When a New Biomarker Wins by Moving Patients Between the Wrong Boxes
A practical guide to net reclassification improvement for clinical researchers. Covers event and non-event NRI, arbitrary risk categories, overtreatment traps, and what reviewers should demand before trusting claims that a new model improved classification.
AI-Assisted Methods Review: What LLMs Can Catch, What They Cannot, and Where Judgment Still Matters
A practical guide to AI-assisted methods review for clinical researchers. Covers where LLMs help with structural critique, where source verification and causal judgment still require humans, and what reviewers should demand before trusting AI-generated methodological comments.
Decision Curve Analysis: When a Better AUC Still Makes Worse Clinical Decisions
A practical guide to decision curve analysis for clinical researchers. Covers net benefit, threshold probability, when prediction models fail to beat treat-all or treat-none strategies, and what reviewers should demand before trusting claims of clinical utility.
Channeling Bias: When the Newer Treatment Inherits the Easier Patients
A practical guide to channeling bias for clinical researchers. Covers preferential prescribing, formulary-era drift, specialist selection, and what reviewers should demand before trusting observational comparisons of newer therapies.
When Death Changes the Question: Competing Risks, Intercurrent Events, and Truncation by Death
A practical guide to the boundary between competing risks, intercurrent events, and truncation by death for clinical researchers. Covers when death changes risk sets, when it makes later outcomes undefined, and what reviewers should demand instead of vague censoring language.
Jump-to-Reference Imputation: When Missing Outcomes Start Borrowing the Control Arm's Future
A practical guide to jump-to-reference imputation for clinical researchers. Covers what J2R assumes after treatment discontinuation, when it helps sensitivity analysis, and when it quietly answers the wrong estimand.
Multiple Testing in Clinical Trials: When One Positive Endpoint Is Just the Loudest Coin Flip
A practical guide to multiple testing in clinical trials for clinical researchers. Covers endpoint families, subgroup fishing, interim looks, alpha control, and what reviewers should demand before trusting a lone positive result.
Confounding by Contraindication: When the Untreated Group Is Too Fragile for the Therapy
A practical guide to confounding by contraindication for clinical researchers. Covers how treatment avoidance in high-risk patients can make therapies look safer or more effective than they are, and what reviewers should demand instead.
Last Observation Carried Forward: When Yesterday's Outcome Pretends the Patient Stopped Changing
A practical guide to last observation carried forward for clinical researchers. Covers why LOCF fails as missing-data strategy, how it can exaggerate or dilute treatment effects, and what reviewers should demand instead.
Time Zero Alignment: When Your Cohort Starts Counting Before Treatment Does
A practical guide to time zero alignment for clinical researchers. Covers eligibility, treatment assignment, delayed initiation, immortal time, and what reviewers should demand before trusting a real-world effect estimate.
Early Stopping for Benefit: When a Trial Quits While the Effect Is Still on Its Best Behavior
A practical guide to early stopping for benefit in clinical trials. Covers interim looks, alpha spending, exaggerated effect sizes, immature follow-up, and what reviewers should demand before trusting a triumphant stop.
Informative Visit Processes: When Who Shows Up Starts Writing the Results
A practical guide to informative visit processes for clinical researchers. Covers endogenous follow-up, unequal observation schedules, visit-triggered outcome capture, inverse-intensity thinking, and what reviewers should demand before trusting longitudinal real-world results.
External Control Arms: When a Comparison Group Arrives from Another Universe
A practical guide to external control arms for clinical researchers. Covers historical and real-world comparators, design drift, prognostic imbalance, endpoint mismatch, and what reviewers should demand before trusting single-arm success stories.
Missing Indicator Method: When an NA Flag Pretends to Be Missing-Data Strategy
A practical guide to the missing-indicator method for clinical researchers. Covers why NA flags fail for confounding control, when they leave residual bias, and what reviewers should demand before trusting a covariate-adjusted result.
Regression to the Mean: When Extreme Patients Improve Before Your Treatment Deserves Credit
A practical guide to regression to the mean for clinical researchers. Covers extreme-baseline selection, before-after mirages, symptom flares, biomarker spikes, and what reviewers should demand before trusting dramatic improvement.
Treatment Switching in Oncology Trials: When Overall Survival Becomes a Rescue Protocol Audit
A practical guide to treatment switching in oncology trials for clinical researchers. Covers crossover, overall survival dilution, ITT versus hypothetical estimands, RPSFTM, IPCW, two-stage estimation, and what reviewers should demand before trusting an adjusted survival claim.
Run-In Periods: When Your Trial Randomizes the Easy Patients First
A practical guide to run-in periods for clinical researchers. Covers adherence enrichment, tolerability selection, estimand drift, external validity, and what reviewers should demand before trusting a polished randomized cohort.
Washout Periods: When “New Use” Is Just Old Use with Better PR
A practical guide to washout periods for clinical researchers. Covers new-user definitions, refill cycles, intermittent treatment, data-history limits, and what reviewers should demand before trusting an incident-user cohort.
Exposure Lagging: When Your Induction Window Becomes Wishful Thinking
A practical guide to exposure lagging for clinical researchers. Covers induction periods, reverse causation, protopathic bias, estimand drift, and what reviewers should demand before trusting a lagged analysis.
Responder Analyses: When a Cutoff Turns a Clinical Gradient into a Headline
A practical guide to responder analyses for clinical researchers. Covers dichotomizing continuous outcomes, post hoc thresholds, baseline dependence, power loss, and what reviewers should demand before trusting "X% achieved response" claims.
Healthy Adherer Bias: When Persistence Looks Like Pharmacology
A practical guide to healthy adherer bias for clinical researchers. Covers why adherent patients often look healthier before the treatment effect is even estimated, how this differs from confounding by indication, and what reviewers should demand before trusting adherence-based benefit claims.
Grace Periods in Target Trial Emulation: Clinical Realism or Future Information in Disguise?
A practical guide to grace periods in target trial emulation for clinical researchers. Covers when a grace window is defensible, when it becomes immortal time in formalwear, and what reviewers should demand before trusting the result.
Index Event Bias: When Your Cohort Already Selected the Wrong Comparison
A practical guide to index event bias for clinical researchers. Covers recurrence-risk paradoxes, conditioning on the first event, secondary prevention cohorts, and what reviewers should demand before trusting protective-looking associations inside diseased cohorts.
Calendar Time Confounding: When Secular Trends Pretend Your Intervention Worked
A practical guide to calendar time confounding for clinical researchers. Covers secular trends, treatment diffusion, concurrent comparators, and what reviewers should demand before trusting real-world benefit that may just reflect a later era.
Surveillance Bias: When One Group Gets More Chances to Become a Case
A practical guide to surveillance bias for clinical researchers. Covers differential testing, follow-up intensity, diagnosis-based outcomes, and what reviewers should demand before trusting higher event rates.
Outcome Switching: When the Primary Endpoint Moves After the Results Get Interesting
A practical guide to outcome switching for clinical researchers. Covers endpoint shopping, selective reporting, protocol drift, and what reviewers should demand before trusting a late-breaking primary outcome.
Overdiagnosis: When Finding More Disease Does Not Mean Saving More Lives
A practical guide to overdiagnosis for clinical researchers. Covers how screening can raise incidence and improve survival statistics without reducing mortality, how to separate lead-time from true overdiagnosis, and what reviewers should demand before trusting the headline.
Lead-Time Bias: When Earlier Diagnosis Pretends to Be Better Survival
A practical guide to lead-time bias for clinical researchers. Covers why screening can improve survival statistics without reducing mortality, how to separate earlier detection from real benefit, and what reviewers should demand before trusting the headline.
Subgroup Analysis: When “Personalized” Findings Are Mostly Multiplicity Wearing a Stethoscope
A practical guide to subgroup analysis for clinical researchers. Covers interaction testing, multiplicity, power failure, post hoc storytelling, and what reviewers should demand before trusting treatment-effect heterogeneity claims.
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