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 philosophical and ancient advancements suitable to causal inference in epidemiology and public future health is additionally supplied. a number of theoretical and utilized elements of causal inference are handled. the purpose of this booklet is not just to summarize very important advancements in causal inference in epidemiology but additionally to spot attainable how one can improve the quest for causal causes for ailments and accidents. Examples are supplied from such fields as continual sickness epidemiology, Veterans well-being, and environmental epidemiology. a specific target of the booklet is to supply principles for strengthening causal inference in epidemiology within the context of sophisticated examine paradigms. those issues are vital as the result of epidemiologic experiences give a contribution to generalizable wisdom by means of clarifying the motives of ailments, by means of combining epidemiologic facts with info from different disciplines (for instance, psychology and business hygiene), through comparing the consistency of epidemiologic facts with etiological hypotheses approximately causation, and through offering the root for comparing systems for healthiness advertising and prevention and public healthiness practices Read more...
1. Foundations --
2. informal inference in epidemiologic study --
3. towards a brand new study paradigm in epidemiology --
4. study paradigms in epidemiology and causal inference.
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Extra resources for Causal inference and scientific paradigms in epidemiology
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” . 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 . However, not all of these criteria need to be satisfied for a causal relationship between an adverse event and a vaccine to be present .