The dubious benefits of multi-level modeling
The dubious benefits of multi-level modeling
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多层次建模的可疑好处
DOI：
10.1080/17437270701383560
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发表时间：
2007
影响因子：
2
通讯作者：
Gorard S
中科院分区：
文献类型：
--
作者：
Gorard S
本文提出了一个反对更广泛地采用复杂形式的数据分析的论点，使用多层次建模（MLM）作为扩展的案例研究。MLM的设计是为了克服现有数据集的一些不足，如聚类造成的偏差。本文认为，传销的理论和实证基础不明确，没有产生重要的实际研究成果，由于有一系列替代方案的可用性，传销在很大程度上是不必要的，因此过于复杂，使得研究报告对普通受众来说难以阅读和理解，没有明显的分析收益。最重要的是，本文通过实例表明，传销在实践中收效甚微，值得我们考虑其分析成本。这些成本包括推广一种教育形式的“星形经济学”，创造不可行的前提，如否认人口数据的存在，以及在每个子层面对大量和少量案例的矛盾需求之间的紧张关系。本文最后概述了大量的替代分析方法，这些方法在检查数据中的结构或克服聚类引起的问题方面与MLM具有相同的效果。许多替代方法更容易使用和理解，不需要专业软件，并且避免了由于使用传销而产生的问题，例如必须忽略丢失变量的情况。
This paper presents an argument against the wider adoption of complex forms of data analysis, using multi‐level modeling (MLM) as an extended case study. MLM was devised to overcome some deficiencies in existing datasets, such as the bias caused by clustering. The paper suggests that MLM has an unclear theoretical and empirical basis, has not led to important practical research results, is largely unnecessary due to the availability of a range of alternatives, and is therefore overly complex, making research reports harder to read and understand for a general audience for no apparent analytic gain. Above all, the paper shows via examples that MLM has made so little difference in practice that it is worth us also considering its analytic costs. These costs include the promotion of an educational form of ‘asterix economics’, the creation of unworkable premises such as denying the existence of population data, and the tension between the contradictory need for both a large and small number of cases at each sub‐level. The paper concludes by outlining a substantial number of alternative methods of analysis which can have the same effect as MLM in examining structures in the data or overcoming the problems caused by clustering. Many of these alternatives are easier to use and understand, do not require specialist software, and avoid the problems—such as having to ignore cases with missing variables—created by the use of MLM.