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The Use of Generalized Linear Models and Generalized Estimating Equations in Bioarchaeological Studies

机译:广义线性模型和广义估计方程在生物考古学中的应用

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The current article explores whether the application of generalized linear models (GLM) and generalized estimating equations (GEE) can be used in place of conventional statistical analyses in the study of ordinal data that code an underlying continuous variable, like entheseal changes. The analysis of artificial data and ordinal data expressing entheseal changes in archaeological North African populations gave the following results. Parametric and nonparametric tests give convergent results particularly for P values <0.1, irrespective of whether the underlying variable is normally distributed or not under the condition that the samples involved in the tests exhibit approximately equal sizes. If this prerequisite is valid and provided that the samples are of equal variances, analysis of covariance may be adopted. GLM are not subject to constraints and give results that converge to those obtained from all nonparametric tests. Therefore, they can be used instead of traditional tests as they give the same amount of information as them, but with the advantage of allowing the study of the simultaneous impact of multiple predictors and their interactions and the modeling of the experimental data. However, GLM should be replaced by GEE for the study of bilateral asymmetry and in general when paired samples are tested, because GEE are appropriate for correlated data.
机译:本文探讨了在编码基本连续变量(如封装变化)的序数数据研究中,是否可以使用广义线性模型(GLM)和广义估计方程(GEE)代替常规统计分析。对表示北非考古人口中的地毯变化的人工数据和有序数据进行的分析得出以下结果。参数测试和非参数测试给出收敛的结果,尤其是对于P值<0.1而言,无论在测试涉及的样本大小近似相等的条件下基础变量是否正态分布。如果此先决条件是有效的,并且前提是样本的方差相等,则可以采用协方差分析。 GLM不受约束,其结果可以收敛于从所有非参数测试中获得的结果。因此,可以使用它们代替传统测试,因为它们可以提供与它们相同的信息量,但是其优点是可以研究多个预测变量及其相互作用的同时影响以及实验数据的建模。但是,对于双边不对称性的研究,一般应在用GEE代替GLM时,因为配对的数据适合用于GEE,因此通常在测试配对样本时使用。

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