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IMF-066-02-0001-en	Which four questions does evidence-based practice separate, and why can a prestigious label answer none of them alone?	Validity, magnitude and uncertainty, applicability, and worth to this patient; a journal, randomised label, small p value, or guideline does not by itself establish any of these.	Integrated Medical Foundations; chapter 66, TTS module 2; https://theisegoria.github.io/medical-textbook/integrated-medical-foundations-expanded-english.md; module SHA256 at export: d88cf1fec87958422c451cce06056462ec01689a969082f64a5a48accf76e65c; editorial review pending	imf lang::en chapter::066 module::066-02 review::pending
IMF-066-02-0002-en	Why can stopping a trial early mislead, and what is checked in the registry and protocol?	Early stopping can lock in a large chance effect; the primary outcome, analysis plan, intended sample size, and follow-up are checked for changes made after results were seen.	Integrated Medical Foundations; chapter 66, TTS module 2; https://theisegoria.github.io/medical-textbook/integrated-medical-foundations-expanded-english.md; module SHA256 at export: d88cf1fec87958422c451cce06056462ec01689a969082f64a5a48accf76e65c; editorial review pending	imf lang::en chapter::066 module::066-02 review::pending
IMF-066-02-0003-en	Why is a baseline significance test not the answer to imbalance in a small randomised trial?	Randomisation does not guarantee balance in small trials; what matters is whether imbalances are clinically important and whether adjusted analysis was prespecified.	Integrated Medical Foundations; chapter 66, TTS module 2; https://theisegoria.github.io/medical-textbook/integrated-medical-foundations-expanded-english.md; module SHA256 at export: d88cf1fec87958422c451cce06056462ec01689a969082f64a5a48accf76e65c; editorial review pending	imf lang::en chapter::066 module::066-02 review::pending
IMF-066-02-0004-en	How do new-user active-comparator designs reduce channeling bias?	Channeling arises when sicker patients preferentially receive one drug; aligning treatment initiation and clinical indication makes the compared groups fairer.	Integrated Medical Foundations; chapter 66, TTS module 2; https://theisegoria.github.io/medical-textbook/integrated-medical-foundations-expanded-english.md; module SHA256 at export: d88cf1fec87958422c451cce06056462ec01689a969082f64a5a48accf76e65c; editorial review pending	imf lang::en chapter::066 module::066-02 review::pending
IMF-066-02-0005-en	How does adjusting for a mediator differ in consequence from conditioning on a collider?	Adjusting for a mediator on the causal path removes part of the effect of interest, while conditioning on a collider caused by two variables creates a false association between them.	Integrated Medical Foundations; chapter 66, TTS module 2; https://theisegoria.github.io/medical-textbook/integrated-medical-foundations-expanded-english.md; module SHA256 at export: d88cf1fec87958422c451cce06056462ec01689a969082f64a5a48accf76e65c; editorial review pending	imf lang::en chapter::066 module::066-02 review::pending
IMF-066-02-0006-en	Why is complete-case analysis often an implausible way to handle missing data?	It assumes that, after conditioning, missingness is unrelated to the unobserved outcome, so reasons for missingness and sensitivity analysis are needed instead.	Integrated Medical Foundations; chapter 66, TTS module 2; https://theisegoria.github.io/medical-textbook/integrated-medical-foundations-expanded-english.md; module SHA256 at export: d88cf1fec87958422c451cce06056462ec01689a969082f64a5a48accf76e65c; editorial review pending	imf lang::en chapter::066 module::066-02 review::pending
IMF-066-02-0007-en	When does an odds ratio approximate a relative risk, and what happens otherwise?	Only when events are uncommon; with common events the odds ratio appears farther from one than the relative risk.	Integrated Medical Foundations; chapter 66, TTS module 2; https://theisegoria.github.io/medical-textbook/integrated-medical-foundations-expanded-english.md; module SHA256 at export: d88cf1fec87958422c451cce06056462ec01689a969082f64a5a48accf76e65c; editorial review pending	imf lang::en chapter::066 module::066-02 review::pending
IMF-066-02-0008-en	Why does non-adherence threaten a non-inferiority trial, and how is this guarded against?	Non-adherence biases toward apparent similarity, so the trial needs a clinically justified margin, reliable active control, preserved conduct, and scrutiny by both intention-to-treat and per-protocol analysis.	Integrated Medical Foundations; chapter 66, TTS module 2; https://theisegoria.github.io/medical-textbook/integrated-medical-foundations-expanded-english.md; module SHA256 at export: d88cf1fec87958422c451cce06056462ec01689a969082f64a5a48accf76e65c; editorial review pending	imf lang::en chapter::066 module::066-02 review::pending
IMF-066-02-0009-en	Why is a single significant secondary outcome after a negative primary outcome likely a chance finding, yet why can strict correction also err?	Many comparisons produce chance positives, but severe multiplicity correction can hide a true signal across related outcomes, so hypothesis families and analysis purposes should be stated.	Integrated Medical Foundations; chapter 66, TTS module 2; https://theisegoria.github.io/medical-textbook/integrated-medical-foundations-expanded-english.md; module SHA256 at export: d88cf1fec87958422c451cce06056462ec01689a969082f64a5a48accf76e65c; editorial review pending	imf lang::en chapter::066 module::066-02 review::pending
IMF-066-02-0010-en	Why can standard Kaplan-Meier methods overestimate the incidence of a nonfatal event?	They treat competing death as ordinary censoring, although death prevents later events such as fracture or dialysis.	Integrated Medical Foundations; chapter 66, TTS module 2; https://theisegoria.github.io/medical-textbook/integrated-medical-foundations-expanded-english.md; module SHA256 at export: d88cf1fec87958422c451cce06056462ec01689a969082f64a5a48accf76e65c; editorial review pending	imf lang::en chapter::066 module::066-02 review::pending
IMF-066-02-0011-en	Give three reasons that lowering a biomarker may fail to help patients.	The marker may not be causal, off-target harms may offset benefit, or timing may differ, so disease-oriented improvement can coexist with worse mortality.	Integrated Medical Foundations; chapter 66, TTS module 2; https://theisegoria.github.io/medical-textbook/integrated-medical-foundations-expanded-english.md; module SHA256 at export: d88cf1fec87958422c451cce06056462ec01689a969082f64a5a48accf76e65c; editorial review pending	imf lang::en chapter::066 module::066-02 review::pending
IMF-066-02-0012-en	How do partial verification and incorporation bias inflate diagnostic accuracy?	Partial verification applies the reference standard only to test-positive patients, and incorporation bias occurs when the index test forms part of the reference diagnosis.	Integrated Medical Foundations; chapter 66, TTS module 2; https://theisegoria.github.io/medical-textbook/integrated-medical-foundations-expanded-english.md; module SHA256 at export: d88cf1fec87958422c451cce06056462ec01689a969082f64a5a48accf76e65c; editorial review pending	imf lang::en chapter::066 module::066-02 review::pending
IMF-066-02-0013-en	How can a prediction model discriminate well yet still be poorly calibrated, and what do internal and external validation test?	It can rank high-risk above low-risk people while overpredicting everyone's risk; internal validation estimates optimism, and external validation tests transport to another setting and time.	Integrated Medical Foundations; chapter 66, TTS module 2; https://theisegoria.github.io/medical-textbook/integrated-medical-foundations-expanded-english.md; module SHA256 at export: d88cf1fec87958422c451cce06056462ec01689a969082f64a5a48accf76e65c; editorial review pending	imf lang::en chapter::066 module::066-02 review::pending
IMF-066-02-0014-en	Why must a time-limited therapeutic trial allow for regression to the mean and similar effects, and what can its result not prove?	Natural variation, regression to the mean, co-interventions, and expectation can create apparent improvement; a before-and-after comparison in one patient does not prove a population causal effect.	Integrated Medical Foundations; chapter 66, TTS module 2; https://theisegoria.github.io/medical-textbook/integrated-medical-foundations-expanded-english.md; module SHA256 at export: d88cf1fec87958422c451cce06056462ec01689a969082f64a5a48accf76e65c; editorial review pending	imf lang::en chapter::066 module::066-02 review::pending