The American journal of drug and alcohol abuse · 2009
Evaluation of heterogeneity in pharmacotherapy trials for drug dependence: a Bayesian approach.
СтатьяПоддержка NIH: внешняя программаПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод пока не подготовлен
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Green C E, Moeller F G, Schmitz J M, Lucke J F, Lane S D, Swann A C, Lasky R E, Carbonari J P
Аннотация
AIMS: Difficulty identifying effective pharmacotherapies for cocaine dependence has led to suggestions that subgroup differences may account for some of the heterogeneity in treatment response. Well-attested methodological difficulties associated with these analyses recommend the use of Bayesian statistical reasoning for evaluation of salient interaction effects.
METHODS: A secondary data analysis of a previously published, double-blind, randomized controlled trial examines the interaction of decision-making, as measured by the Iowa Gambling Task, and citalopram in increasing longest sustained abstinence from cocaine use.
RESULTS: Bayesian analysis indicated that there was a 99% chance that improved decision-making enhances response to citalopram. Given the strong positive nature of this finding, a formal, quantitative Bayesian approach to evaluate the result from the perspective of a skeptic was applied.
CONCLUSIONS: Bayesian statistical reasoning provides a formal means of weighing evidence for the presence of an interaction in scenarios where conventional, Frequentist analyses may be less informative. [Supplementary materials are available for this article. Go to the publisher's online edition of The American Journal of Drug and Alcohol Abuse for the following free supplemental resource: Appendix 1].
METHODS: A secondary data analysis of a previously published, double-blind, randomized controlled trial examines the interaction of decision-making, as measured by the Iowa Gambling Task, and citalopram in increasing longest sustained abstinence from cocaine use.
RESULTS: Bayesian analysis indicated that there was a 99% chance that improved decision-making enhances response to citalopram. Given the strong positive nature of this finding, a formal, quantitative Bayesian approach to evaluate the result from the perspective of a skeptic was applied.
CONCLUSIONS: Bayesian statistical reasoning provides a formal means of weighing evidence for the presence of an interaction in scenarios where conventional, Frequentist analyses may be less informative. [Supplementary materials are available for this article. Go to the publisher's online edition of The American Journal of Drug and Alcohol Abuse for the following free supplemental resource: Appendix 1].