Conditional Model Selection in Mixed-Effects Models with cAIC4
Journal of Statistical Software, 2021 Model selection in mixed models based on the conditional distribution is appropriate for many practical applications and has been a focus of recent statistical research.
Benjamin Säfken +3 more
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Multivariate Survival Mixed Models for Genetic Analysis of Longevity Traits [PDF]
, 2014 A class of multivariate mixed survival models for continuous and discrete time with a complex covariance structure is introduced in a context of quantitative genetic applications.
Labouriau, Rodrigo +2 more
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An application of mixed-effect models to analyse contraceptive use in Malawian women
Contraception and Reproductive Medicine, 2019 In Malawi, the current approach to family planning using contraceptive methods is individualised, yet studies have shown that variability in contraceptive-use still remains after accounting for it at individual and household levels. Therefore, this study
Davis James Makupe +2 more
doaj +1 more source
Bench Plot and Mixed Effects Models: First steps toward a comprehensive benchmark analysis toolbox [PDF]
, 2008 Benchmark experiments produce data in a very specific format. The observations are drawn from the performance distributions of the candidate algorithms on resampled data sets.
Eugster, Manuel J. A., Leisch, Friedrich
core +1 more source
Derivative Computations and Robust Standard Errors for Linear Mixed Effects Models in lme4 [PDF]
, 2017 While robust standard errors and related facilities are available in R for many types of statistical models, the facilities are notably lacking for models estimated via lme4.
Merkle, Edgar C., Wang, Ting
core +3 more sources
Mixed Effects in Stochastic Differential Equation Models
Revstat Statistical Journal, 2005 A class of statistical models is proposed where random effects are incorporated into a stochastic differential equations model, and an expression for the likelihood function is derived.
Susanne Ditlevsen , Andrea De Gaetano
doaj +1 more source
Linear Mixed Models with Marginally Symmetric Nonparametric Random Effects
, 2016 Linear mixed models (LMMs) are used as an important tool in the data analysis of repeated measures and longitudinal studies. The most common form of LMMs utilize a normal distribution to model the random effects.
McLachlan, Geoffrey J., Nguyen, Hien D.
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Generalizing across stimuli as well as subjects: A non-mathematical tutorial on mixed-effects models [PDF]
Tutorials in Quantitative Methods for Psychology, 2016 Although it has long been known that analyses that treat stimuli as a fixed effect do not permit generalization from the sample of stimuli to the population of stimuli, surprisingly little attention has been paid to this issue outside of the field of ...
Chang, Yu-Hsuan A., Lane, David M.
doaj +1 more source
Logistic mixed models to investigate implicit and explicit belief tracking [PDF]
, 2016 We investigated the proposition of a two-systems Theory of Mind in adults’ belief tracking. A sample of N = 45 participants predicted the choice of one of two opponent players after observing several rounds in an animated card game. Three matches of this
Lages, Martin, Scheel, Anne
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Bayesian Linear Mixed Models with Polygenic Effects
Journal of Statistical Software, 2018 We considered Bayesian estimation of polygenic effects, in particular heritability in relation to a class of linear mixed models implemented in R (R Core Team 2018).
Jing Hua Zhao +2 more
doaj +1 more source