Partitioning variation in multilevel models

By Harvey Goldstein, William J. Browne, J. Rasbash. 2002

851 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Management Science and Operations Research, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/0e5cdb0e7b8762fb6f3572119f4776b234d6f184

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In Computer Networks and Communications

In Management Science and Operations Research

In Statistics and Probability

Citations in the corpus

Appropriate assessment of neighborhood effects on individual health: integrating random and fixed effects in multilevel logistic regression. (2005, background): “Nevertheless, intraclass correlations have serious interpretational drawbacks ( 10 ) for binary responses.”
Repeatability for Gaussian and non‐Gaussian data: a practical guide for biologists (2010, methodology): “The repeatability can also be calculated on the original (proportion) scale (Browne et al., 2005; Goldstein et al., 2002): RpropM = σ 2 α ·P2/(1 + exp(β0))2 σ 2α ·P2/(1 + exp(β0))2 + ω·P (1 − P ) , (16) P = exp(β0) 1 + exp(β0) (17) where RpropM is the proportion-scale repeatability estimated from…”
A statistical framework to explore ontogenetic growth variation among individuals and populations: a marine fish example (2015, methodology): “Firstly, we calculated the intraclass correlation coefficient (ICC), representing the degree of correlation among growth increments from individuals in a Year or Cohort group for model 2a and 2b (intercept-only models to ensure the interpretability of variance components; Goldstein et al. 2002).”
Income inequality and health: what have we learned so far? (2004, methodology): “† This coefficient refers to the % of variation that is attributable to states estimated from a two-level binomial logistic model when a variance component estimated at the state level is based on the “latent variable approach” method ( 73 ).”
The coefficient of determination R2 and intra-class correlation coefficient from generalized linear mixed-effects models revisited and expanded (2016, neutral): “I n t e r f a c e 14 : 20170213 also [33]).”
The complexity of school and neighbourhood effects and movements of pupils on school differences in models of educational achievement (2009, background): “223, giving a variance partition coefficient (Goldstein et al., 2002) of 0.”
Mixed and Mixture Regression Models for Continuous Bounded Responses Using the Beta Distribution (2012, methodology): “In a two-level model, following Goldstein et al.’s (2002) first-order Taylor expansion of the location submodel, our adaptation of their formulation yields the following approximate estimate of the Level 2 variance,”
Assessing the measurement properties of neighborhood scales: from psychometrics to ecometrics. (2007, background): “Decomposition of variance in these models is not straightforward, because the level 1 variance depends on the covariates and because the level 1 variance and the levels 2 and 3 variances are on different scales ( 43 , 44).”
Does satisfactory neighbourhood environment lead to a satisfying life? An investigation of the association between neighbourhood environment and life satisfaction in Beijing (2017, neutral): “The importance of the unobservable effect is quantified by using the variance partitioning coefficient ( σ u 2 /( σ u 2 + π 2 /3)) ( Goldstein et al., 2002).”