Literature DB >> 21908418

Accounting for perception, placebo and unmasking effects in estimating treatment effects in randomised clinical trials.

Farid Jamshidian1, Alan E Hubbard1, Nicholas P Jewell2.   

Abstract

There is a rich literature on the role of placebos in experimental design and evaluation of therapeutic agents or interventions. The importance of masking participants, investigators and evaluators to treatment assignment (treatment or placebo) has long been stressed as a key feature of a successful trial design. Nevertheless, there is considerable variability in the technical definition of the placebo effect and the impact of treatment assignments being unmasked. We suggest a formal concept of a 'perception effect' and define unmasking and placebo effects in the context of randomised trials. We employ modern tools from causal inference to derive semi-parametric estimators of such effects. The methods are illustrated on a motivating example from a recent pain trial where the occurrence of treatment-related side effects acts as a proxy for unmasking.
© The Author(s) 2011 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.

Entities:  

Keywords:  Direct causal effects; G-computation; maximum likelihood estimation; pain studies; perception effect; placebo effect; semi-parametric estimation; targeted maximum likelihood estimation; unblinding; unmasking effect

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Year:  2011        PMID: 21908418      PMCID: PMC9170117          DOI: 10.1177/0962280211413449

Source DB:  PubMed          Journal:  Stat Methods Med Res        ISSN: 0962-2802            Impact factor:   2.494


  19 in total

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5.  Developing Placebos for Clinical Research in Traditional Chinese Medicine: Assessing Organoleptic Properties of Three Dosage Forms (Oral Liquid, Capsule and Granule).

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