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Arts Assignment代写:历史概念
2017-02-15 12:57
产生的历史概念与广义科克伦曼特尔Haenzel是1950年代末的流。科克伦(1958),一个伟大的统计学家之一,首先引入了一个测试来确定独立的多个2×2表通过扩展一般为独立的一个双向表卡方检验。在这里,每个表由一个或两个额外的变量为高水平检测多级性质。测试数据是基于每个表的行总数。背后的假设是细胞计数有二项分布。 为一个扩展科克伦的作品,壁炉架和Haenzel(1959)扩展科克伦的检验统计量为行和列总数的假设细胞计数每个表遵循hypergeommetric分布。自科克伦曼特尔Hanzel(不啻)统计主要限制二进制数据,兰迪斯et al(1978)广义这个测试处理超过两个级别。但是有一个主要缺点的广义科克伦曼特尔Haenzel(GCMH)测试。这个测试是无法处理集群相关分类数据。梁(1985)提出了一个检验统计量为摆脱这个问题。然而,测试数据本身的主要问题,无法使用。 作为统计的发展领域,需要一个检验统计量能够处理相关数据和变量引起较高的水平。张和嘘声(1995)进入该领域,介绍了三种测试统计电话TP和你解决上面的问题。然而这三个测试数据之间TP和你喜欢电话,因为这两个使用单个对象作为初级抽样单位,而电话使用地层作为初级抽样单位(De Silva Sooriyarachchi,2012)。 TP的此外,通过模拟研究显示更好的性能比TE通过保持其误差值即使地层都很小,它使用池估计方差。因此,它提供了一个指南选择TP作为最合适的统计进行这项研究。德席尔瓦和Sooriyarachchi(2012)开发了一个R程序进行这个测试。Arts Assignment代写:历史概念
The history of arising the concepts related to Generalized Cochran Mantel Haenzel was streaming to the late 1950’s. Cochran (1958), one of a great Statistician has firstly introduced a test to identify the independence of multiple 2 × 2 tables by extending the general chi-square test for independence of a single 2-way table. In here, the each table consists of one or two additional variables for higher levels to detect the multilevel nature. The test statistic is based on the row totals of each table. The assumption behind is that the cell counts have binomial distribution.
As an extension to Cochran’s work, Mantel and Haenzel (1959) extended the Cochran’s test statistic for both row and column totals by assuming the cell counts of each table follows a hypergeommetric distribution. Since Cochran Mantel Hanzel (CMH) statistic has a major limitation on binary data, Landis et al (1978) generalized this test into handle more than two levels. However there is a major drawback of the Generalized Cochran Mantel Haenzel (GCMH) test. This test was unable to handle clustered correlated categorical data. Liang (1985) was proposed a test statistic for get rid of this problem. However that test statistic itself had major problems and it was fail to use.
As development of the statistics field, a need for a test statistic capable of handling correlated data and variables with higher levels arouse. Zhang and Boos (1995) coming in to the field and introduced three test statistics TEL TP and TU as a solution to the above problems. However among these three test statistics TP and TU are preferred to TEL since these two use the individual subjects as the primary sampling units while TEL use the strata as the primary sampling unit (De Silva and Sooriyarachchi, 2012).
Furthermore, by a simulation study TP shows better performance than TE by maintaining its error values even when the strata are small and it uses the pooled estimators for variance. Therefore it provides a guideline to select TP as the most suitable statistic to perform this study. De Silva and Sooriyarachchi (2012) developed a R program to carry out this test.
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