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The coefficient of determination R 2 and intra-class correlation coefficient from generalized linear mixed-effects models revisited and expanded

https://doi.org/10.1101/095851
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What this work says

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Modern Applied Statistics with S
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Likelihood-based and Bayesian methods for Tweedie compound Poisson linear mixed models
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Generalized linear mixed models: a practical guide for ecology and evolution
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Data Analysis Using Regression and Multilevel/Hierarchical Models
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A marginal quasi-likelihood approach to the analysis of Poisson variables with generalized linear mixed models
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A Note on the Delta Method
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Who Invented the Delta Method?
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Double Exponential Families and Their Use in Generalized Linear Regression
inferredcites →https://doi.org/10.1080/02664763.2016.1193725openalex-snapshot
AnR2statistic for fixed effects in the generalized linear mixed model
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AD Model Builder: using automatic differentiation for statistical inference of highly parameterized complex nonlinear models
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APPROXIMATING VARIANCE OF DEMOGRAPHIC PARAMETERS USING THE DELTA METHOD: A REFERENCE FOR AVIAN BIOLOGISTS
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R$^{2}$s for Correlated Data: Phylogenetic Models, LMMs, and GLMMs
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Modeling zero-inflated count data with glmmTMB
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Using commonality analysis in multiple regressions: a tool to decompose regression effects in the face of multicollinearity
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Extension of Nakagawa & Schielzeth's R2GLMM to random slopes models
inferredcites →https://doi.org/10.1111/2041-210x.12512openalex-snapshot
piecewiseSEM : Piecewise structural equation modelling in r for ecology, evolution, and systematics
inferredcites →https://doi.org/10.1111/j.1467-985x.2004.00365.xopenalex-snapshot
Variance Partitioning in Multilevel Logistic Models that Exhibit Overdispersion
inferredcites →https://doi.org/10.1111/j.1469-185x.2010.00141.xopenalex-snapshot
Repeatability for Gaussian and non‐Gaussian data: a practical guide for biologists
inferredcites →https://doi.org/10.1111/j.1541-0420.2009.01335.xopenalex-snapshot
A Generalized Concordance Correlation Coefficient Based on the Variance Components Generalized Linear Mixed Models for Overdispersed Count Data
inferredcites →https://doi.org/10.1111/j.2041-210x.2012.00261.xopenalex-snapshot
A general and simple method for obtaining R 2 from generalized linear mixed‐effects models
inferredcites →https://doi.org/10.1177/1094428113493929openalex-snapshot
Understanding the Results of Multiple Linear Regression
inferredcites →https://doi.org/10.1177/1094428114541701openalex-snapshot
Explained Variance Measures for Multilevel Models
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Partitioning Variation in Multilevel Models
inferredcites →https://doi.org/10.1515/9781400840908openalex-snapshot
Ecological Models and Data in R
inferredcites →https://doi.org/10.1534/genetics.115.186536openalex-snapshot
General Methods for Evolutionary Quantitative Genetic Inference from Generalized Mixed Models
inferredcites →https://doi.org/10.1890/06-1714.1openalex-snapshot
ESTIMATING TREND PRECISION AND POWER TO DETECT TRENDS ACROSS GROUPED COUNT DATA
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QUASI-POISSON VS. NEGATIVE BINOMIAL REGRESSION: HOW SHOULD WE MODEL OVERDISPERSED COUNT DATA?
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Models for Longitudinal Data: A Generalized Estimating Equation Approach
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Unrepeatable Repeatabilities: A Common Mistake
inferredcites →https://doi.org/10.2527/1997.75176xopenalex-snapshot
Genetic analysis of discrete reproductive traits in sheep using linear and nonlinear models: I. Estimation of genetic parameters.
inferredcites →https://doi.org/10.3168/jds.s0022-0302(99)75415-9openalex-snapshot
Genetic Analysis of Fertility in Dairy Cattle Using Negative Binomial Mixed Models
inferredcites →https://doi.org/10.3929/ethz-b-000105397openalex-snapshot
Fitting Linear Mixed-Effects Models Using lme4
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A comparison of observation-level random effect and Beta-Binomial models for modelling overdispersion in Binomial data in ecology & evolution
inferredcites →https://doi.org/10.7717/peerj.616openalex-snapshot
Using observation-level random effects to model overdispersion in count data in ecology and evolution

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