Mastering variation: variance components and personalised medicine

Various sources of variation in observed response in clinical trials and clinical practice are considered, and ways in which the corresponding components of variation might be estimated are discussed. Although the issues have been generally well‐covered in the statistical literature, they seem to be...

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Veröffentlicht in:Statistics in medicine 2016-03, Vol.35 (7), p.966-977
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description Various sources of variation in observed response in clinical trials and clinical practice are considered, and ways in which the corresponding components of variation might be estimated are discussed. Although the issues have been generally well‐covered in the statistical literature, they seem to be poorly understood in the medical literature and even the statistical literature occasionally shows some confusion. To increase understanding and communication, some simple graphical approaches to illustrating issues are proposed. It is also suggested that reducing variation in medical practice might make as big a contribution to improving health outcome as personalising its delivery according to the patient. It is concluded that the common belief that there is a strong personal element in response to treatment is not based on sound statistical evidence. © 2015 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd.
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source MEDLINE; Wiley Online Library Journals Frontfile Complete
subjects Analysis of Variance
Asthma - physiopathology
Asthma - therapy
Biostatistics
Clinical medicine
Clinical trials
Clinical Trials as Topic - statistics & numerical data
Communication
components of variation
Computer Graphics
Computer Simulation
Cross-Over Studies
cross-over trials
Forced Expiratory Volume
Humans
n-of-1 trials
personalised medicine
Precision Medicine - statistics & numerical data
random effects
Randomized Controlled Trials as Topic - statistics & numerical data
Special Issue Paper
Special Issue Papers
Tonsillectomy - statistics & numerical data
title Mastering variation: variance components and personalised medicine
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