title: Evaluation of heterogeneity in pharmacotherapy trials for drug dependence: a Bayesian approach.
abstract: OBJECTIVE
  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].
authors.affiliation: Center for Clinical Research & Evidence-Based Medicine, University of Texas, Houston, 77030, USA. Charles.Green@uth.tmc.edu
authors.forename: C E
authors.initials: CE
authors.lastname: Green
authors.forename: F G
authors.initials: FG
authors.lastname: Moeller
authors.forename: J M
authors.initials: JM
authors.lastname: Schmitz
authors.forename: J F
authors.initials: JF
authors.lastname: Lucke
authors.forename: S D
authors.initials: SD
authors.lastname: Lane
authors.forename: A C
authors.initials: AC
authors.lastname: Swann
authors.forename: R E
authors.initials: RE
authors.lastname: Lasky
authors.forename: J P
authors.initials: JP
authors.lastname: Carbonari