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首页> 外文期刊>Journal of Clinical and Diagnostic Research >Categorical Data Analysis: Fundamentals and Perspective Applications in Health Sciences
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Categorical Data Analysis: Fundamentals and Perspective Applications in Health Sciences

机译：分类数据分析：卫生科学的基础知识和前景应用

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This paper introduces the statistical methods for testing differences between paired categorical responses. Application of the independent sample tests while analysing paired data is observed among health science researchers. Four common tests are described in detail for identifying specific differences between pairs of groups. Situation to use each test is discussed in general and in comparison with others. Almost all statistical analysis techniques involve assumptions about the data to be analysed. The paired situation tests including paired t-test and repeated measures analysis of variance requires the distribution of the differences be approximately normal, on the other hand, the unpaired t-test requires an assumption of normality to hold separately for both groups of observations. The data analysis technique also requires an assumption regarding the data generation process. Categorical data analysis approaches provide a series of statistical methods that require limited assumptions on the data. The tests more commonly used are McNemar?s, and Cochran?s Q, while some are not so widely reported, like Stuart Maxwell McNemar?s, and Cochran Mantel Haenszel correlation method.
机译：本文介绍了用于检验配对类别响应之间差异的统计方法。在健康科学研究人员中观察到在分析配对数据时应用独立样本测试。详细描述了四种常见的测试，以识别成对的组之间的特定差异。一般讨论了每种测试的使用情况，并与其他测试进行了比较。几乎所有的统计分析技术都涉及要分析的数据的假设。配对状态测试（包括配对t检​​验和方差的重复测量分析）要求差异的分布近似正态，另一方面，未配对t检验则需要假设正态性才能分别适用于两组观察值。数据分析技术还需要有关数据生成过程的假设。分类数据分析方法提供了一系列统计方法，这些方法需要对数据进行有限的假设。较常用的测试是McNemar？s和Cochran？s Q，而有些则未得到广泛报道，例如Stuart Maxwell McNemar？s和Cochran Mantel Haenszel相关法。

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