Abstract Previous theoretical and empirical research on register variation has argued that linguistic co-occurrence patterns have a highly systematic relationship to register differences, because they both share the same functional underpinnings. The goal of this study is to test this claim through a comparison of two statistical techniques that have been used to describe register variation: factor analysis (as used in Multi-Dimensional analysis, MDA) and canonical discriminant analysis (CDA). MDA and CDA have different statistical bases and thus give priority to different analytical considerations: linguistic co-occurrence in the case of MDA and the prediction of register differences in the case of CDA. Thus, there is no statistical reason to expect that the two techniques, if applied to the same corpus, will produce similar results. We hypothesize that although MDA and CDA approach register variation from opposite sides, they will produce similar results because both types of statistical patterns are motivated by underlying discourse functions. The present paper tests this claim through a case-study analysis of variation among web registers, applying MDA and CDA to analyze register variation in the same corpus of texts.

中文翻译：

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所有的道路都通向罗马吗？：用因子分析和判别分析对寄存器变化建模

摘要先前有关寄存器变异的理论和实证研究认为，语言共现模式与寄存器差异具有高度系统的关系，因为它们都具有相同的功能基础。这项研究的目的是通过比较两种用于描述寄存器变化的统计技术来检验这一主张：因子分析（用于多维分析，MDA）和规范判别分析（CDA）。MDA和CDA具有不同的统计基础，因此优先考虑不同的分析考虑因素：在MDA中，语言共现，在CDA中，预测寄存器差异。因此，没有统计理由可以预期，如果将这两种技术应用于同一语料库，将产生相似的结果。我们假设，尽管MDA和CDA方法记录了相反方面的差异，但它们会产生相似的结果，因为这两种类型的统计模式都是受潜在话语功能的驱动。本文通过对Web寄存器中变量的案例研究分析，应用MDA和CDA来分析同一文本语料库中的寄存器变量来测试此要求。