A practical guide to multilevel modeling
A practical guide to multilevel modeling
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DOI：
10.1016/j.jsp.2009.09.002
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发表时间：
2010-02-01
影响因子：
5
通讯作者：
Peugh, James L.
中科院分区：
文献类型：
--
作者：
Peugh, James L.
从教室或学校内的学生收集数据，并随着时间的推移从学生油多个场合收集数据，是教育研究中使用的两种常见的抽样方法，通常需要多层次建模（MLM）数据分析技术，以避免类型1错误。本文的目的是阐明多水平分析中涉及的七个主要步骤：（1）阐明研究问题，（2）选择适当的参数估计，（3）评估MLM的必要性，（4）建立1级模型，（5）建立2级模型，（6）多水平效应量报告，（7）似然比模型检验。这七个步骤都说明了横截面和纵向传销的例子，从国家教育纵向研究（NELS）数据集。本文的目的是帮助应用研究人员进行和解释多层次分析，并提供建议，以指导报告传销分析结果。(C)2009年学校心理学研究学会。由爱思唯尔有限公司出版。保留所有权利。
Collecting data from students within classrooms or schools, and collecting data from students oil multiple occasions over time, are two common sampling methods used in educational research that often require multilevel modeling (MLM) data analysis techniques to avoid Type-1 errors. The purpose of this article is to clarify the seven major steps involved in a multilevel analysis: (1) clarifying the research question, (2) choosing the appropriate parameter estimator, (3) assessing the need for MLM, (4) building the level-1 model, (5) building the level-2 model, (6) multilevel effect size reporting, and (7) likelihood ratio model testing. The seven steps are illustrated with both a cross-sectional and a longitudinal MLM example from the National Educational Longitudinal Study (NELS) dataset. The goal of this article is to assist applied researchers in conducting and interpreting multilevel analyses and to offer recommendations to guide the reporting of MLM analysis results. (C) 2009 Society for the Study of School Psychology. Published by Elsevier Ltd. All rights reserved.