The effect of random-effects misspecification on classification accuracy [PDF]
The International Journal of Biostatistics, 2021 Abstract Mixed models are a useful way of analysing longitudinal data. Random effects terms allow modelling of patient specific deviations from the overall trend over time. Correlation between repeated measurements are captured by specifying a joint distribution for all random effects in a model.
Riham El Saeiti +2 more
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Extension of Nakagawa & Schielzeth's R2GLMM to random slopes models [PDF]
, 2014 1.Nakagawa & Schielzeth extended the widely used goodness-of-fit statistic R2 to apply to generalized linear mixed models (GLMMs). However, their R2GLMM method is restricted to models with the simplest random effects structure, known as random ...
Johnson, Paul C.D.
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Misspecification in Generalized Linear Mixed Models and Its Impact on the Statistical Wald Test
Applied Sciences, 2023 Generalized linear mixed models are commonly used in repeated measurement studies and account for the dependence between observations obtained from the same experimental unit.
Diana Arango-Botero +2 more
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Statistical Inference of Wiener Constant-Stress Accelerated Degradation Model with Random Effects
Mathematics, 2022 In the field of reliability analysis, the constant-stress accelerated degradation test is one of the most commonly used methods to evaluate a product’s reliability as degradation data are provided. In this paper, a constant-stress accelerated degradation
Peihua Jiang
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A Bayesian localised conditional auto-regressive model for estimating the health effects of air pollution [PDF]
, 2013 Estimation of the long-term health effects of air pollution is a challenging task, especially when modeling spatial small-area disease incidence data in an ecological study design.
Besag +19 more
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The effect of splitting on random forests [PDF]
Machine Learning, 2014 The effect of a splitting rule on random forests (RF) is systematically studied for regression and classification problems. A class of weighted splitting rules, which includes as special cases CART weighted variance splitting and Gini index splitting, are studied in detail and shown to possess a unique adaptive property to signal and noise. We show for
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Modelling the distribution of health related quality of life of advancedmelanoma patients in a longitudinal multi-centre clinical trial using M-quantile random effects regression [PDF]
, 2018 Health-related quality of life assessment is important in the clinical evaluation of patients with metastatic disease that may offer useful information in understanding the clinical effectiveness of a treatment.
Bianco, Paola Del +4 more
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Revstat Statistical Journal, 2018 The generalized linear mixed effects model (GLMM) approach is widely used to analyze longitudinal binary data when the goal of the study is a subject-specific interpretation because it allows missing values on the response, provided they are missing at ...
M. Salomé Cabral +1 more
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Effective Bi-immunity and Randomness [PDF]
, 2016 We study the relationship between randomness and effective bi-immunity. Greenberg and Miller have shown that for any oracle X, there are arbitrarily slow-growing DNR functions relative to X that compute no ML random set. We show that the same holds when ML randomness is replaced with effective bi-immunity.
Achilles A. Beros +2 more
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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
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