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Tree Height Prediction Using a Double Hidden-Layer Neural Network and a Mixed-Effects Model [PDF]
PlantsThe double hidden-layer neural network has increasingly been applied in tree height modeling due to its superior performance. To improve the precision of tree height estimation, this study compared the performance of a double hidden-layer neural network ...
Jianbo Shen +4 more
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A Method to Explore the Best Mixed-Effects Model in a Data-Driven Manner with Multiprocessing: Applications in Public Health Research [PDF]
European Journal of Investigation in Health, Psychology and EducationIn the present study, I developed and tested an R module to explore the best models within the context of multilevel modeling in research in public health. The module that I developed, explore.models, compares all possible candidate models generated from
Hyemin Han
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Model Specification in Mixed-Effects Models
Communications in Kinesiology, 2023 Mixed-effect models are flexible tools for researchers in a myriad of fields, but that flexibility comes at the cost of complexity and if users are not careful in how their model is specified, they could be making faulty inferences from their data.
Keith Lohse +2 more
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Mixed-effect models with trees
Advances in Data Analysis and Classification, 2022 AbstractTree-based regression models are a class of statistical models for predicting continuous response variables when the shape of the regression function is unknown. They naturally take into account both non-linearities and interactions. However, they struggle with linear and quasi-linear effects and assume iid data.
Anna Gottard +3 more
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Decentralized Mixed Effects Modeling in COINSTAC
Neuroinformatics, 2023 Abstract Performing group analysis on magnetic resonance imaging (MRI) data with linear mixed-effects (LME) models is challenging due to its large dimensionality and inherent multi-level covariance structure. In addition, as large-scale collaborative projects become commonplace in neuroimaging, data must increasingly ...
Sunitha Basodi +7 more
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Frontiers in Genetics, 2022 Dynamic changes of microbiome communities may play important roles in human health and diseases. The recent rise in longitudinal microbiome studies calls for statistical methods that can model the temporal dynamic patterns and simultaneously quantify the
Linchen He +7 more
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Stat, 2020 When multiple measures are collected repeatedly over time, redundancy typically exists among responses. The envelope method was recently proposed to reduce the dimension of responses without loss of information in regression with multivariate responses. It can gain substantial efficiency over the standard least squares estimator.
Yuyang Shi, Linquan Ma, Lan Liu
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Applying Linear Mixed Effects Models with Crossed Random Effects to Psycholinguistic Data: Multilevel Specification and Model Selection. [PDF]
Tutorials in Quantitative Methods for Psychology, 2015 Applying linear mixed effects regression (LMER) models to psycholinguistic data was made popular by Baayen, Davidson, and Bates (2008). However, applied researchers sometimes encounter model specification difficulties when using such models.
Hsiu-Ting Yu
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Frontiers in Microbiology, 2022 The Pacific Northwest (PNW) is one of the largest commercial harvesting areas for Pacific oysters (Crassostrea gigas) in the United States. Vibrio parahaemolyticus, a bacterium naturally present in estuarine waters accumulates in shellfish and is a major
Brendan Fries +9 more
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One-factor model for default rates by loan type [PDF]
Bankarstvo, 2021 This paper investigates the link between default rates by loan types and the systemic credit risk component. This link is described by a linear model that combines systemic and idiosyncratic contributions.
Božović Miloš
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