Statistical methods in randomised controlled trials for delirium

Farewell, Daniel ORCID: https://orcid.org/0000-0002-8871-1653, Tahir, Tayyeb A. and Bisson, Jonathan Ian ORCID: https://orcid.org/0000-0001-5170-1243 2012. Statistical methods in randomised controlled trials for delirium. Journal of Psychosomatic Research 73 (3) , pp. 197-204. 10.1016/j.jpsychores.2012.06.002

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Abstract

Objective The analysis of clinical trials in delirium is typically complicated by treatment dropouts and by the fact that even untreated individuals may have a good prognosis. These features of delirium trials warrant special statistical attention; implications for each stage of a trial planning process are described. Methods Choice of outcome, patient sample, and data collection in delirium trials are discussed. Descriptions are given, together with examples, of time-to-event, imputation-based, linear and nonlinear models for the analysis of randomised controlled trials for delirium. Results Imputation allows evaluation of the plausibility of individual recovery trajectories, but some simple imputations are found to be unsuitable for delirium research. Time-to-event and nonlinear models encourage a global perspective on analysis, which is often preferable to cross-sectional end-of-trial assessments. It is suggested that nonlinear random effects models for longitudinal trajectories are particularly suitable in a delirium context. Conclusion It is hoped that the methods described, and nonlinear models in particular, will play a part in convincing analyses of future delirium research.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	MRC Centre for Neuropsychiatric Genetics and Genomics (CNGG) Medicine
Subjects:	H Social Sciences > HA Statistics R Medicine > R Medicine (General) R Medicine > RC Internal medicine > RC0321 Neuroscience. Biological psychiatry. Neuropsychiatry R Medicine > RM Therapeutics. Pharmacology
Uncontrolled Keywords:	Delirium ; Nonlinear models ; Randomised controlled trials; Statistical methods
Publisher:	Elsevier
ISSN:	0022-3999
Last Modified:	21 Oct 2022 09:44
URI:	https://orca.cardiff.ac.uk/id/eprint/37489

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