LEVEL (Logical Explanations & Visualizations of Estimates in Linear mixed models): Recommendations for reporting multilevel data and analyses

Maria Jose Monsalves; Ananta Shrikant Bangdiwala; Alex Thabane; Shrikant Ishver Bangdiwala

doi:10.1186/s12874-019-0876-8

LEVEL (Logical Explanations & Visualizations of Estimates in Linear mixed models): Recommendations for reporting multilevel data and analyses

Maria Jose Monsalves, Ananta Shrikant Bangdiwala, Alex Thabane, Shrikant Ishver Bangdiwala^*

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

55 Scopus citations

Original language	English
Article number	3
Journal	BMC Medical Research Methodology
Volume	20
Issue number	1
DOIs	https://doi.org/10.1186/s12874-019-0876-8
State	Published - 2020

ASJC Scopus subject areas

Epidemiology
Health Informatics

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10.1186/s12874-019-0876-8

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title = "LEVEL (Logical Explanations & Visualizations of Estimates in Linear mixed models): Recommendations for reporting multilevel data and analyses",

keywords = "Multilevel diagram, Multilevel models, Reporting guidelines, Variance partition coefficients",

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AU - Monsalves, Maria Jose

AU - Bangdiwala, Ananta Shrikant

AU - Thabane, Alex

AU - Bangdiwala, Shrikant Ishver

PY - 2020/1/6

Y1 - 2020/1/6

KW - Multilevel diagram

KW - Multilevel models

KW - Reporting guidelines

KW - Variance partition coefficients

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LEVEL (Logical Explanations & Visualizations of Estimates in Linear mixed models): Recommendations for reporting multilevel data and analyses

ASJC Scopus subject areas

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