Testing Equality in Ordinal Data with Repeated Measurements: A Model-Free Approach

IF 1.2 4区数学

International Journal of Biostatistics Pub Date : 2016-11-01 DOI:10.1515/ijb-2015-0075

K. Lui

引用次数: 1

Abstract

Abstract In randomized clinical trials, we often encounter ordinal categorical responses with repeated measurements. We propose a model-free approach with using the generalized odds ratio (GOR) to measure the relative treatment effect. We develop procedures for testing equality of treatment effects and derive interval estimators for the GOR. We further develop a simple procedure for testing the treatment-by-period interaction. To illustrate the use of test procedures and interval estimators developed here, we consider two real-life data sets, one studying the gender effect on pain scores on an ordinal scale after hip joint resurfacing surgeries, and the other investigating the effect of an active hypnotic drug in insomnia patients on ordinal categories of time to falling asleep.

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用重复测量检验有序数据的相等性:一种无模型方法

在随机临床试验中，我们经常遇到重复测量的顺序分类反应。我们提出了一种无模型的方法，使用广义优势比(GOR)来衡量相对治疗效果。我们开发了检验治疗效果相等性的程序，并推导了GOR的区间估计。我们进一步开发了一个简单的程序来测试按周期治疗的相互作用。为了说明测试程序和区间估计器的使用，我们考虑了两个现实生活中的数据集，一个研究性别对髋关节表面置换手术后疼痛评分的顺序影响，另一个研究失眠患者的有效催眠药物对入睡时间的顺序影响。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

International Journal of Biostatistics Mathematics-Statistics and Probability

CiteScore

2.30

自引率

8.30%

发文量

期刊介绍： The International Journal of Biostatistics (IJB) seeks to publish new biostatistical models and methods, new statistical theory, as well as original applications of statistical methods, for important practical problems arising from the biological, medical, public health, and agricultural sciences with an emphasis on semiparametric methods. Given many alternatives to publish exist within biostatistics, IJB offers a place to publish for research in biostatistics focusing on modern methods, often based on machine-learning and other data-adaptive methodologies, as well as providing a unique reading experience that compels the author to be explicit about the statistical inference problem addressed by the paper. IJB is intended that the journal cover the entire range of biostatistics, from theoretical advances to relevant and sensible translations of a practical problem into a statistical framework. Electronic publication also allows for data and software code to be appended, and opens the door for reproducible research allowing readers to easily replicate analyses described in a paper. Both original research and review articles will be warmly received, as will articles applying sound statistical methods to practical problems.