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Data Collectionhard
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An observational study of smoking and lung cancer risk enrolls 600 smokers and 600 matched non-smokers, balanced on 12 measured confounders (age, SES, air pollution, diet, alcohol use, occupational exposures, etc.). The matched analysis yields:

Conditional odds ratio: 2.4 (smokers have 2.4× higher odds of lung cancer)

A Rosenbaum sensitivity analysis assesses robustness to an unmeasured confounder. The analysis finds:

"If a hidden binary confounder increased both smoking odds and lung cancer odds by a factor of Γ ≥ 2.8, it could entirely explain the observed association under the null hypothesis of no true smoking effect."

Which statement correctly interprets this finding?

A) The unmeasured confounder definitely exists; the smoking effect is spurious
B) The observed effect is robust to unmeasured confounding only if no such confounder with Γ ≥ 2.8 in both directions exists
C) An unmeasured confounder of size Γ = 2.8 is implausibly large; the smoking–cancer association is causal
D) Sensitivity analysis proves that smoking causes lung cancer in matched data