Variance partitioning in multilevel logistic models that exhibit overdispersion

By William J. Browne, S. Subramanian, Kelvyn Jones, Harvey Goldstein. 2005

434 citations recorded by the source corpus.

Subfields: Plant Science, Sociology and Political Science, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/23cb95dac21ce261b5f3268de477e9f5236ab988

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Citations in the corpus

Empirical prediction models for the coverage and yields of cowberry in Finland. (2013, methodology): “As suggested by Browne et al. (2005), overdispersion in the response variables was taken into account by adding an additional random term in the models (“pseudo” level).”
A brief conceptual tutorial of multilevel analysis in social epidemiology: linking the statistical concept of clustering to the idea of contextual phenomenon (2005, neutral): “38 39 Appropriate measures are, however, already available, 20 35 40–43 and we explain these measures in a What this paper adds N We provide a link—comprehensible to epidemiolo-gists—between multilevel regression techniques and social epidemiological concepts, particularly the analogy between the…”
Multimodel inference in ecology and evolution: challenges and solutions (2011, methodology): “Additionally, in GLMM analysis, the residual variance of nonGaussian data may be modelled as either multiplicative overdispersion (the overdispersion parameter which appears in QAIC, see Table 1) or additive overdispersion (a residual variance as in linear mixed models; see Browne et al., 2005).”
Estimated transmissibility and impact of SARS-CoV-2 lineage B.1.1.7 in England (2021, methodology): “These analyses included sample date as a continuous covariate, region (or state) as a fixed factor (for Switzerland) or random intercept (for Denmark and the USA), and an observation-level random effect to take into account overdispersion (54).”
A multilevel modelling approach to investigating the predictive validity of editorial decisions: do the editors of a high profile journal select manuscripts that are highly cited after publication? (2011, neutral): “The variance partition coefficient (Browne et al., 2005) is only 0.05 (= σ̂2u0=.σ̂2u0 +3:29)).”
Intermediate and advanced topics in multilevel logistic regression analysis (2017, methodology): “Nevertheless, there are a variety of procedures for calculating the VPC for binary responses, including a normal response approximation, the simulation method, the Taylor series linearization, and the latent response formulation [5,15,25,26].”
Mixed and Mixture Regression Models for Continuous Bounded Responses Using the Beta Distribution (2012, background): “Browne et al. (2005) extend their approach to mixed models with more than two levels.”
Repeatability for Gaussian and non‐Gaussian data: a practical guide for biologists (2010, methodology): “For example, if we are interested in measurement errors (precisions of measurements), we want to know the repeatability on the original scale rather than the latent scale (for relevant discussions, see Browne et al., 2005; Visscher et al., 2008).”
The coefficient of determination R2 and intra-class correlation coefficient from generalized linear mixed-effects models revisited and expanded (2016, positive): “Alternatively, 86 overdispersion in GLMMs can be implemented using a multiplicative overdispersion term [14].”