Article ID: CBB518937449

Causal inference in biomedical research (2020)

unapi

Current debates surrounding the virtues and shortcomings of randomization are symptomatic of a lack of appreciation of the fact that causation can be inferred by two distinct inference methods, each requiring its own, specific experimental design. There is a non-statistical type of inference associated with controlled experiments in basic biomedical research; and a statistical variety associated with randomized controlled trials in clinical research. I argue that the main difference between the two hinges on the satisfaction of the comparability requirement, which is in turn dictated by the nature of the objects of study, namely homogeneous or heterogeneous populations of biological systems. Among other things, this entails that the objection according to which randomized experiments fail to provide better evidence for causation because randomization cannot guarantee comparability is mistaken.

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Authors & Contributors
Prince, Brian D.
Hankinson, Robert J.
Holmes, Brooke
Broadbent, Alex
Baetu, Tudor M.
Handerer, Fritz
Journals
Studies in History and Philosophy of Science Part C: Studies in History and Philosophy of Biological and Biomedical Sciences
History of Psychiatry
British Journal for the History of Philosophy
Biology and Philosophy
NTM: Zeitschrift für Geschichte der Naturwissenschaften, Technik und Medizin
Apeiron: Journal for Ancient Philosophy and Science
Publishers
Palgrave Macmillan
Oxford University Press
Concepts
Philosophy of medicine
Biomedicine
Causality
Disease and diseases
Psychiatry
Nosology; classification of diseases
People
Plato
Galen
Mitscherlich, Alexander
Time Periods
21st century
Ancient
19th century
20th century
20th century, late
20th century, early
Places
Greece
Wales
England
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