Linear and Generalized Linear Mixed Models and Their Applications

By Donald E. Myers. Technometrics, 2008

526 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/0d9ea3956243696a4fd9bc399fe96f15331c7680

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Statistics and Probability

Citations in the corpus

Mixed model prediction and small area estimation (2006, methodology): “Because of the great volume of research in mixed models, we cannot claim the completeness of the literature review on mixed models and refer the interested readers to the upcoming monograph by Jiang (2006b).”
Model Selection in Linear Mixed Models (2013, methodology): “Jiang, Nguyen and Rao (2009) suggest calculating for each M ∈ M the bootstrapped probability p∗(M ; cn) = P(M0(cn) =M), whereM0(cn) is the optimal model satisfying (32).”
Best Predictive Small Area Estimation (2011, methodology): “There are several ways of deriving the BLUP (e.g., Jiang 2007, p. 76), but at least one standard procedure is the following.”
Generalized fiducial inference for normal linear mixed models (2012, background): “…, i = 1, . . . , a, j = 1, . . . , ni,(2.2) with unknown mean μ, random effect α ∼ N(0, σ 2α ) where σ 2α is unknown, a is the number of levels of α, ni is the number of observations in level i and error terms εij ∼ N(0, σ 2ε ) where σ 2ε is also unknown, and α and ε are independent [Jiang (2007)].”
Empirical Evaluation of Hierarchical Ground‐Motion Models: Score Uncertainty and Model Weighting (2017, methodology): “…N ground motions predicted forM earthquakes are EQ-TARGET;temp:intralink-;df6;313;613 y N×1 N p N×1 ; V N×N N XM i Ni V N×N R N×N Z N×M G M×M Z′ R diag R;…;RM ; similarly for G and Z 6 (Jiang, 2007, his equation 1.4), in which diag · denotes a block diagonal matrix, and Z′ is the transpose of Z.”
Epigenetic correlates of plant phenotypic plasticity: DNA methylation differs between prickly and nonprickly leaves in heterophyllous Ilex aquifolium (Aquifoliaceae) trees (2013, methodology): “…2010; Herrera et al., 2012) is well suited to test for the significance of effects of interest on mean per-marker methylation probability because of the property of linear models of taking into account the uncertainty in the dependent variable arising from unobservable random errors (Jiang, 2007).”
Two Tweedie distributions that are near‐optimal for modelling monthly rainfall in Australia (2011, background): “• All exponential dispersion models that are closed with respect to scale transformations are Tweedie models (Jorgensen, 1997; Jiang, 2007); that is, if Y is from a particular Tweedie distribution with index p and c is some constant, then cY is also from the same Tweedie distribution.”
To transform or not to transform: using generalized linear mixed models to analyse reaction time data (2015, background): “To achieve these goals, GLMMs require the researcher to consider these issues as part of the specification process.”