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- W4296801009 abstract "Abstract The odds ratio (OR) has been misunderstood in evidence based medicine and clinical epidemiology. Currently, “noncollapsibility” is considered a problem with interpretation of the OR and it is thought that the OR is rarely the parameter of interest for causal inference or interpretation of effect modification. The current focus on the relative risk ( RR ) and risk difference ( RD ) suffers from an important limitation: they are not solely measures of effect and vary numerically with baseline risk. In this paper, generalized linear models are examined in terms of the three binary effect measures commonly used in epidemiology to demonstrate that OR s may be the only way to interpret effect modification and have properties that should make them the parameter of interest for causal inference. We look forward to discussion, debate, and counter‐views on this issue from the epidemiology community." @default.
- W4296801009 created "2022-09-24" @default.
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- W4296801009 date "2022-09-01" @default.
- W4296801009 modified "2023-09-30" @default.
- W4296801009 title "Redefining effect modification" @default.
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- W4296801009 doi "https://doi.org/10.1111/jebm.12495" @default.
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