The environment and disease¶
Hill, A. B. (1965). The environment and disease: Association or causation?. Proceedings of the Royal Society of Medicine, 58(5), 295-300.
Cited by¶
4 citations across 4 artifacts.
Each citation links to the sentence it supports in the citing article.
Primes¶
- Causality
- Epidemiology codifies causal reasoning in Bradford-Hill criteria for inferring causation from association: strength of association, dose-response, temporal ordering, consistency across studies, biological plausibility, coherence with existing theory, experimental evidence, specificity, and analogy to known causal pathways.
This sourceThe Presidential Address that sets out the nine viewpoints (strength, consistency, specificity, temporality, biological gradient, plausibility, coherence, experiment, analogy) for inferring causation from association.
- Epidemiology codifies causal reasoning in Bradford-Hill criteria for inferring causation from association: strength of association, dose-response, temporal ordering, consistency across studies, biological plausibility, coherence with existing theory, experimental evidence, specificity, and analogy to known causal pathways.
- Confounding
This sourceArticulates the nine viewpoints (strength, consistency, specificity, temporality, biological gradient, plausibility, coherence, experiment, analogy) for inferring causation from epidemiological association. (Bibliography only — link added.)
- Dose-Response Relationship
- Not a causal claim without experimental structure: a dose-response curve derived from observational data without exposure control is susceptible to confounding; the construct's full inferential force depends on experimental or quasi-experimental design—a recognition Hill (1965) codified in his canonical criteria for distinguishing association from causation, where "biological gradient" (a coherent dose-response curve) is one of nine criteria, none individually sufficient.
This sourceArticulates nine viewpoints (strength, consistency, specificity, temporality, biological gradient, plausibility, coherence, experiment, analogy) for inferring causation from association; supports D47-021 (biological gradient / dose-response as one of nine criteria, none individually sufficient).
- Not a causal claim without experimental structure: a dose-response curve derived from observational data without exposure control is susceptible to confounding; the construct's full inferential force depends on experimental or quasi-experimental design—a recognition Hill (1965) codified in his canonical criteria for distinguishing association from causation, where "biological gradient" (a coherent dose-response curve) is one of nine criteria, none individually sufficient.
- Experimental Design
- Experimental design clarifies the relationship between research questions, causal claims, and data structure, a clarification Hill (1965) advanced in his classic enumeration of criteria for causal inference.
This sourcearticulates nine criteria/viewpoints (strength, consistency, specificity, temporality, biological gradient, plausibility, coherence, experiment, analogy) for inferring causation from epidemiological association.
- Experimental design clarifies the relationship between research questions, causal claims, and data structure, a clarification Hill (1965) advanced in his classic enumeration of criteria for causal inference.
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