Original paper
Quantifying explained variance in multilevel models: An integrative framework for defining R-squared measures.
Abstract
Researchers often mention the utility and need for R-squared measures of explained variance for multilevel models (MLMs). Although this topic has been addressed by methodologists, the MLM R-squared literature suffers from several shortcomings: (a) analytic relationships among existing measures have not been established so measures equivalent in the population have been redeveloped 2 or 3 times; (b) a completely full partitioning of variance has...
Paper Details
Title
Quantifying explained variance in multilevel models: An integrative framework for defining R-squared measures.
Published Date
Jun 1, 2019
Journal
Volume
24
Issue
3
Pages
309 - 338
Citation AnalysisPro
You’ll need to upgrade your plan to Pro
Looking to understand the true influence of a researcher’s work across journals & affiliations?
- Scinapse’s Top 10 Citation Journals & Affiliations graph reveals the quality and authenticity of citations received by a paper.
- Discover whether citations have been inflated due to self-citations, or if citations include institutional bias.
Notes
History