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Applying Hierarchical Linear Modeling (HLM) to Social Work Administration Research

机译:层次线性建模(HLM)在社会工作管理研究中的应用

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摘要

Multi-level structures are common in social work administration research, where individuals are hierarchically nested within organizations. Hierarchical linear modeling (HLM) is a statistical method developed to address issues associated with the unique nature of multilevel data. We introduce the basic notion of HLM, highlighting the need for using this technique in multilevel data. We also present analytical procedures, illustrating the major issues involved in the application of HLM to social work administration research. Currently, there has been an increasing interest in promoting a multilevel approach in social work administration research. To comprehend and benefit from the results of research dealing with the multilevel approach, administrators as well as researchers are expected to understand the basic logic of HLM. This paper delivers sufficient practical knowledge for research consumers to appreciate the results of research that has employed HLM, especially for those consumers who are not familiar with advanced statistics.
机译:多层结构在社会工作管理研究中很常见,其中个人分层地嵌套在组织内。分层线性建模(HLM)是一种统计方法,旨在解决与多级数据的独特性质相关的问题。我们介绍了HLM的基本概念,强调了在多级数据中使用此技术的必要性。我们还提供了分析程序,说明了将HLM应用于社会工作管理研究中涉及的主要问题。当前,对在社会工作管理研究中推广多层次方法的兴趣日益浓厚。为了理解和受益于涉及多级方法的研究结果,管理人员和研究人员应理解HLM的基本逻辑。本文为研究消费者提供了足够的实践知识,使他们能够欣赏采用HLM的研究成果,特别是对于那些不熟悉高级统计信息的消费者。

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