Journal
REVIEW OF EDUCATIONAL RESEARCH
Volume 79, Issue 1, Pages 69-102Publisher
SAGE PUBLICATIONS INC
DOI: 10.3102/0034654308325581
Keywords
hierarchical modeling; statistics; data analysis
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This study analyzed the reporting of multilevel modeling applications of a sample of 99 articles from 13 peer-reviewed journals in education and the social sciences. A checklist, derived from the methodological literature oil multilevel modeling and focusing on the issues of model development and specification, data considerations, estimation, and inference, was used to analyze the articles. The most common applications were two-level models where individuals were nested within contexts. Most studies were non-experimental and used nonprobability samples. The amount of data at each level varied widely across studies, as did the number of models examined. Analyses of reporting practices indicated some clear problems, with man v articles riot reporting enough information for a reader to critique the reported analyses. For example, in many articles, one could not determine how many models were estimated, what covariance structure was assumed, what type of centering if any was used, whether the data were consistent with assumptions, whether outliers were present. or how the models were estimated. Guidelines for researchers reporting multilevel analyses are provided.
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