Understanding hierarchical linear models: Applications in nursing research
Understanding hierarchical linear models: Applications in nursing research
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DOI：
10.1097/01.nnr.0000280634.71278.a0
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发表时间：
2007-07-01
期刊：
影响因子：
2.5
通讯作者：
Derksen, Linda
中科院分区：
文献类型：
--
作者：
Adewale, Adeniyi J.;Hayduk, Leslie;Derksen, Linda
护士在等级组织和职业结构中执业。因此，从护理环境中产生的数据是结构化的，通常是固有的，分层的。从普通回归的角度来看，这种结构构成了一个统计问题，因为这违背了我们观察到独立且相同的情况的假设。一种较好的方法是采用与护理环境中存在的自然聚集相匹配的分析方法。因此，由于这种强大的分析数据结构，人们对将分层或多层线性模型应用于护理环境的兴趣越来越大。本文的目的是促进对分层模型的优点和局限性的理解。一个假设的护理例子从最基本的层次线性模型逐步扩展到一个完整的两层模型。指出了两层模型和三层模型在结构上的相似之处，同时着重于模型的层次性质，而不是统计技术。文中还讨论了层次模型的局限性。
Nurses practice within hierarchical organizations and occupational structure. Hence, data emanating from nursing environments are structured, often inherently, hierarchically. From the perspective of ordinary regression, such structuring constitutes a statistical problem because this violates the assumption that we have observed independent and identical cases. A preferable approach is to employ analytical methods that mesh with the kinds of natural aggregations present in nursing environments. Consequently, there has been increasing interest in applying hierarchical, or multilevel, linear models to nursing contexts because this powerful analytical data structure. The purpose of this article is to foster an understanding of both the strengths and limitations of hierarchical model. A hypothetical nursing example is progressively extended from the most basic hierarchical linear model toward a full two-level model. The structural similarities between two-level and three-level models are pointed out while focusing on the hierarchical nature of models rather than statistical technicalities. The limitations of hierarchical models are discussed also.