Single patient (n-of-1) trials with binary treatment preference
The use of a fully parametric Bayesian method for analysing single patient trials based on the notion of treatment ‘preference’ is described. This Bayesian hierarchical modelling approach allows for full parameter uncertainty, use of prior information and the modelling of individual and patient sub‐...
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| Veröffentlicht in: | Statistics in medicine 2005-09, Vol.24 (17), p.2625-2636 |
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| container_title | Statistics in medicine |
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| creator | Schluter, P. J. Ware, R. S. |
| description | The use of a fully parametric Bayesian method for analysing single patient trials based on the notion of treatment ‘preference’ is described. This Bayesian hierarchical modelling approach allows for full parameter uncertainty, use of prior information and the modelling of individual and patient sub‐group structures. It provides updated probabilistic results for individual patients, and groups of patients with the same medical condition, as they are sequentially enrolled into individualized trials using the same medication alternatives. Two clinically interpretable criteria for determining a patient's response are detailed and illustrated using data from a previously published paper under two different prior information scenarios. Copyright © 2005 John Wiley & Sons, Ltd. |
| doi_str_mv | 10.1002/sim.2132 |
| format | Article |
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| ispartof | Statistics in medicine, 2005-09, Vol.24 (17), p.2625-2636 |
| issn | 0277-6715 1097-0258 |
| language | eng |
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| source | MEDLINE; Wiley Online Library Journals Frontfile Complete |
| subjects | Amitriptyline - therapeutic use Analgesics, Non-Narcotic - therapeutic use Bayes Theorem Bayesian analysis binomial Clinical trials Fibromyalgia - drug therapy hierarchical Bayesian methods Humans informative priors Models, Statistical N-of-1 Numerical Analysis, Computer-Assisted Probability Randomized Controlled Trials as Topic - methods single patient trials treatment preference treatment responder |
| title | Single patient (n-of-1) trials with binary treatment preference |
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