New Testing Methodology for Ordered Categorical Data

经典的治疗评估方案是给一组人服用安慰剂，再给另一组人服用安慰剂。通常，反应变量是一个有序的分类变量，如无改善、部分改善、完全恢复。研究人员感兴趣的是回答这个问题：治疗是否比对照组“更好”？许多针对这个问题的推荐测试程序被发现存在不足。其中包括似然比检验和Wilcoxon-Mann， Whitney检验。这项研究包括对“更好”的各种定义的回顾和改进测试程序的发展。新的程序是计算机辅助的，并显示出良好的理论和实际性能。确定新产品或新治疗或新方法是否优于标准是包括生物技术，材料，制造和社会科学在内的各个领域的基本问题。目前用于在这些情况下做出决定的方法被认为是不合适的，或者在许多情况下，它们检测优质产品的能力较弱。研究人员基于一种新的方法来研究决策程序，这种方法有效地消除了以前方法的缺点。理论论证和广泛的数值计算支持了这些发现，并证明了改进的幅度。

Cohen and Sackrowitz 9618715 A classical protocol for the evaluation of a treatment is to administer a placebo to a set of individuals and administer the treatment to another set of individuals. Oftentimes the response variable is an ordered categorical variable such as no improvement, partial improvement, complete recovery. The researcher is interested in answering the question: Is the treatment "better" than the control? Many recommended testing procedures that are directed towards this question are found to be wanting. Among these are the likelihood ratio test and the Wilcoxon-Mann, Whitney test. The research involves a review of various definitions of "better" and the development of improved testing procedures. The new procedures are computer assisted and are shown to have desirable theoretical and practical properties. The determination of whether or not a new product or new treatment or new method is better than a standard is a fundamental issue in a variety of areas including biotechnology, materials, manufacturing, and the social sciences. Current methods used to make decisions in these situations are found to be either inappropriate or, in many instances, weak in their ability to detect a superior product. The investigators study decision procedures based on a new approach which is effective in eliminating the shortcomings of previous methods. Theoretical arguments as well as extensive numerical calculations support the findings and demonstrate the magnitude of the improvements.