Baetu, Tudor (2020) Causal Inference in Biomedical Research. [Preprint]

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Abstract

Causation can be inferred by two distinct patterns of reasoning, each requiring a distinct experi-mental design. Common, non-statistical causal inference is associated with controlled experi-ments in basic biomedical research. Statistical inference is associated with Randomized Con-trolled Trials in clinical research. The main difference between the two patterns of inference hinges on the satisfaction of a comparability requirement, which is in turn dictated by the nature of the objects of study, namely homogeneous vs. heterogeneous populations of biological sys-tems. This distinction entails that the objection according to which randomized experiments fail to provide better evidence for causation because randomization cannot guarantee comparability is mistaken. As far as the validity of the statistical inference is concerned, randomization is not re-quired in order to ensure comparability, but rather to prevent systematic bias which may com-promise the accuracy of the intervention.

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Item Type:	Preprint
Creators:	Creators Email ORCID Baetu, Tudor tbaetu@hotmail.com 0000-0002-5544-1773
Keywords:	Randomization Controlled experiment RCT Experimental science
Subjects:	General Issues > Causation Specific Sciences > Medicine > Clinical Trials General Issues > Experimentation
Depositing User:	Tudor Baetu
Date Deposited:	28 Jul 2020 03:53
Last Modified:	28 Jul 2020 03:53
Item ID:	17674
Subjects:	General Issues > Causation Specific Sciences > Medicine > Clinical Trials General Issues > Experimentation
Date:	2020
URI:	https://philsci-archive.pitt.edu/id/eprint/17674

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