Causal inference and scientific paradigms in epidemiology by Steven Coughlin

By Steven Coughlin

This anthology of articles on causal inference and medical paradigms in epidemiology covers numerous very important subject matters together with the hunt for causal reasons, the strengths and boundaries of causal standards, quantitative techniques for assessing causal relationships which are proper to epidemiology and rising paradigms in epidemiologic learn. in an effort to offer ancient context, an outline of  Read more...

Pt --
1. Foundations --
pt --
2. informal inference in epidemiologic study --
pt --
3. towards a brand new study paradigm in epidemiology --
pt --
4. study paradigms in epidemiology and causal inference.

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Causal inference and scientific paradigms in epidemiology

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Int J Epidemiol 2008;37:120-32. Halloran ME, Struchiner CJ. Causal inference in infectious diseases. Epidemiology 1995;6:142-51. Strom BL, Ed. Pharmacoepidemiology, 3rd ed. , 2000. Shakir SAW, Layton D. Causal association in pharmacovigilance and pharmacoepidemiology. Thoughts on the application of the Austin Bradford-Hill criteria. Drug Safety 2002:25:467-71. Susser E, Schwartz S. Are social causes so different from all other causes? A comment on Sander Greenland. Emerg Themes Epidemiol 2005;2:4.

Austin PC. The performance of different propensity score methods for estimating marginal odds ratios. Stat Med 2007;26:3078-94. Austin PC. The performance of different propensity-score methods for estimating relative risks. J Clin Epidemiol 2008;61:537-45. Stuart EA. Developing practical recommendations for the use of propensity scores: discussion of ‘A critical appraisal of propensity score matching in the medical literature between 1996 and 2003’ by Peter Austin. Stat Med 2008;27:2062-5. Shah BR, Laupacis A, Hux JE, Austin PC.

Finally, Strom noted that “A dose-response relationship is an extremely important and commonly used concept in clinical pharmacology and is used similarly in epidemiology” [16]. 0 for adverse drug reactions. 0) are also needed in pharmacoepidemiology [16, 17]. Criteria such as strength of the association, consistency, specificity, temporal relation, and biological plausibility have also been used to assess the causality of adverse events following immunization [27]. However, not all of these criteria need to be satisfied for a causal relationship between an adverse event and a vaccine to be present [27].

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