Testing equality and interval estimation in binary responses when high dose cannot be used first under a three-period crossover design.
When comparing two doses of a new drug with a placebo, we may consider using a crossover design subject to the condition that the high dose cannot be administered before the low dose. Under a random-effects logistic regression model, we focus our attention on dichotomous responses when the high dose cannot be used first under a three-period crossover trial. We derive asymptotic test procedures for testing equality between treatments. We further derive interval estimators to assess the magnitude of the relative treatment effects. We employ Monte Carlo simulation to evaluate the performance of these test procedures and interval estimators in a variety of situations. We use the data taken as a part of trial comparing two different doses of an analgesic with a placebo for the relief of primary dysmenorrhea to illustrate the use of the proposed test procedures and estimators.
a Department of Mathematics and Statistics , College of Sciences, San Diego State University , San Diego , California , USA.
Kung-Jong
KJ
Lui
Kuang-Chao
KC
Chang
D000700:Analgesics / Q000008:administration & dosage; D003198:Computer Simulation; D018592:Cross-Over Studies; D004412:Dysmenorrhea / Q000188:drug therapy; D005260:Female; D006801:Humans; D016014:Linear Models; D016015:Logistic Models; D015233:Models, Statistical; D009010:Monte Carlo Method; D016017:Odds Ratio; D016032:Randomized Controlled Trials as Topic / Q000706:statistics & numerical data*; D016896:Treatment Outcome
D000700:Analgesics
Binary data; Crossover trial; Equality; Interval estimation; Titration trial