Hypothesis testing and estimation in ordinal data under a simple crossover design.
Since each patient serves as his/her own control, the crossover design can be of use to improve power as compared with the parallel-groups design in studying noncurative treatments to certain chronic diseases. Although the research studies on the crossover design have been quite intensive, the discussions on analyzing ordinal data under such a design are truly limited. We propose using the generalized odds ratio (GOR) for paired sample data to measure the relative effect on patient responses for both treatment and period in ordinal data under a simple crossover trial. Assuming the treatment and period effects are multiplicative, we note that one can easily derive the maximum likelihood estimator (LE) in closed forms for the GOR of treatment and period effects. We develop asymptotic and exact procedures for testing treatment and period effects. We further derive asymptotic and exact interval estimators for the GOR of treatment and period effects. We use the data taken from a crossover trial to assess the clarity of leaflet instructions between two devices among asthma patients to illustrate the use of these test procedures and estimators developed here.
Department of Mathematics and Statistics, College of Sciences, San Diego State University, San Diego, California 92182-7720, USA. kjl@rohan.sdsu.edu
Kung-Jong
KJ
Lui
Kuang-Chao
KC
Chang
D000280:Administration, Inhalation; D018927:Anti-Asthmatic Agents / Q000008:administration & dosage / Q000627:therapeutic use; D001249:Asthma / Q000188:drug therapy; D018592:Cross-Over Studies; D003627:Data Interpretation, Statistical; D006801:Humans; D015233:Models, Statistical; D009330:Nebulizers and Vaporizers / Q000592:standards; D016017:Odds Ratio; D011356:Product Labeling; D016032:Randomized Controlled Trials as Topic / Q000379:methods* / Q000706:statistics & numerical data*; D018401:Sample Size; D016896:Treatment Outcome
D018927:Anti-Asthmatic Agents