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LEVEL (Logical Explanations & Visualizations of Estimates in Linear mixed models)
recommendations for reporting multilevel data and analyses
Monsalves, M. J., Bangdiwala, A. S., Thabane, A., & Bangdiwala, S. I. (2020). LEVEL (Logical Explanations & Visualizations of Estimates in Linear mixed models): recommendations for reporting multilevel data and analyses. BMC Medical Research Methodology, 20(1), Article 3. https://doi.org/10.1186/s12874-019-0876-8
A standardized checklist for the reporting of multilevel data and the presentation of linear mixed models will promote adequate reporting of correlated data analyses. In this manuscript, we propose LEVEL (Logical Explanations & Visualizations of Estimates in Linear mixed models), a systematic approach for the presentation of studies with correlated data from multilevel study designs, with an accompanying checklist for standardizing the reporting of results from linear mixed models. These models are quite complex, and the intention of this manuscript is not to be a statistical tutorial, but to mention aspects of the study design and analysis methods that we propose should be addressed in a publication. We present the basics of a linear mixed model simply to introduce the terminology and to help understand the proposed reporting recommendations.