Quantifying explained variance in multilevel models: An integrative framework for defining R-squared measures.
Sign Up to like & getrecommendations! Published in 2019 at "Psychological methods"
DOI: 10.1037/met0000184
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… read more here.
Keywords: framework; explained variance; variance; variance multilevel ... See more keywords
An Investigation of Factored Regression Missing Data Methods for Multilevel Models with Cross-Level Interactions.
Sign Up to like & getrecommendations! Published in 2023 at "Multivariate behavioral research"
DOI: 10.1080/00273171.2022.2147049
Abstract: A growing body of literature has focused on missing data methods that factorize the joint distribution into a part representing the analysis model of interest and a part representing the distributions of the incomplete predictors.… read more here.
Keywords: missing data; investigation factored; factored regression; multilevel models ... See more keywords
On the Common but Problematic Specification of Conflated Random Slopes in Multilevel Models.
Sign Up to like & getrecommendations! Published in 2023 at "Multivariate behavioral research"
DOI: 10.1080/00273171.2023.2174490
Abstract: For multilevel models (MLMs) with fixed slopes, it has been widely recognized that a level-1 variable can have distinct between-cluster and within-cluster fixed effects, and that failing to disaggregate these effects yields a conflated, uninterpretable… read more here.
Keywords: conflation; conflated random; random component; multilevel models ... See more keywords
Re-assessing the Consistency of Sentencing Decisions in Cases of Assault: Allowing for Within-Court Inconsistencies
Sign Up to like & getrecommendations! Published in 2020 at "British Journal of Criminology"
DOI: 10.1093/bjc/azaa030
Abstract: Empirical research has repeatedly focused on the potential existence of sentencing disparities. In particular, a growing number of studies have used multilevel models to quantify the extent that ‘similar’ offences are treated alike in different… read more here.
Keywords: court; within court; assessing consistency; cases assault ... See more keywords
Catching Up on Multilevel Modeling.
Sign Up to like & getrecommendations! Published in 2022 at "Annual review of psychology"
DOI: 10.1146/annurev-psych-020821-103525
Abstract: This review focuses on the use of multilevel models in psychology and other social sciences. We target readers who are catching up on current best practices and sources of controversy in the specification of multilevel… read more here.
Keywords: multilevel modeling; multilevel; catching multilevel; multilevel models ... See more keywords
Meta-Analysis of Single-Case Research via Multilevel Models: Fundamental Concepts and Methodological Considerations
Sign Up to like & getrecommendations! Published in 2018 at "Behavior Modification"
DOI: 10.1177/0145445518806867
Abstract: Multilevel modeling is an approach that can be used to summarize single-case experimental design (SCED) data. Multilevel models were developed to analyze hierarchical structured data with units at a lower level nested within higher level… read more here.
Keywords: single case; multilevel; meta analysis; multilevel models ... See more keywords
Drawing Generalizable Conclusions From Multilevel Models: Commentary on
Sign Up to like & getrecommendations! Published in 2024 at "Psychological Science"
DOI: 10.1177/09567976241245411
Abstract: In a recently published article, Van de Calseyde and Efendić (2022) argue that inner-crowd wisdom (i.e., the reduction in error afforded by aggregating two estimates from a given person relative to a single initial estimate… read more here.
Keywords: conclusions multilevel; generalizable conclusions; multilevel models; van calseyde ... See more keywords
On Ignoring the Random Effects Assumption in Multilevel Models: Review, Critique, and Recommendations
Sign Up to like & getrecommendations! Published in 2019 at "Organizational Research Methods"
DOI: 10.1177/1094428119877457
Abstract: Entities such as individuals, teams, or organizations can vary systematically from one another. Researchers typically model such data using multilevel models, assuming that the random effects are uncorrelated with the regressors. Violating this testable assumption,… read more here.
Keywords: effects assumption; models review; assumption multilevel; ignoring random ... See more keywords
Effect size measures for multilevel models: definition, interpretation, and TIMSS example
Sign Up to like & getrecommendations! Published in 2018 at "Large-scale Assessments in Education"
DOI: 10.1186/s40536-018-0061-2
Abstract: Effect size reporting is crucial for interpretation of applied research results and for conducting meta-analysis. However, clear guidelines for reporting effect size in multilevel models have not been provided. This report suggests and demonstrates appropriate… read more here.
Keywords: interpretation; size measures; effect size; effect ... See more keywords
Using Multilevel Models and Generalized Estimating Equation Models to Account for Clustering in Neurology Clinical Research
Sign Up to like & getrecommendations! Published in 2024 at "Neurology"
DOI: 10.1212/wnl.0000000000209947
Abstract: In clinical and health services research, clustered data (also known as data with a multilevel or hierarchical structure) are frequently encountered. For example, patients may be clustered or nested within hospitals. Understanding when data have… read more here.
Keywords: multilevel models; neurology; generalized estimating; account clustering ... See more keywords
Local influence diagnostics in elliptical multilevel models.
Sign Up to like & getrecommendations! Published in 2025 at "Anais da Academia Brasileira de Ciencias"
DOI: 10.1590/0001-3765202520240796
Abstract: Local influence diagnostics for elliptical multilevel models are proposed in this paper. This class of models involves the use of continuous symmetric distributions, including heavy-tailed error models, and the normal distribution as a particular case.… read more here.
Keywords: multilevel models; elliptical multilevel; diagnostics elliptical; influence ... See more keywords