title: Use of a stochastic model for repeated binary assessment.
abstract: We discuss a stochastic model appropriate for binary data in clinical studies where assessments are made at various nominal times during a treatment phase. The model is then applied to data on headache relief, nausea and photophobia/phonophobia in a migraine study. The transition rates and probabilities during the initial 240 minutes after treatment administration are derived using the method of maximum likelihood. The results are then compared with analysis at each nominal time point. Stochastic modelling is considered more appropriate for the analysis of repeated binary assessments than analysis at each nominal time since each patient's assessments are modelled simultaneously.
authors.affiliation: Glaxo Wellcome Research and Development, Middlesex, U.K.
authors.forename: H
authors.initials: H
authors.lastname: Hassani
authors.forename: A
authors.initials: A
authors.lastname: Ebbutt
mesh_terms: D003627:Data Interpretation, Statistical; D006801:Humans; D008027:Light; D016013:Likelihood Functions; D008390:Markov Chains; D008881:Migraine Disorders / Q000150:complications / Q000175:diagnosis / Q000188:drug therapy; D015233:Models, Statistical; D009325:Nausea / Q000209:etiology / Q000517:prevention & control; D011336:Probability; D016032:Randomized Controlled Trials as Topic / Q000379:methods*; D012008:Recurrence; D013016:Sound; D016896:Treatment Outcome