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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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Applied Sciences, 2022 MR scans of low-gamma X-nuclei, low-concentration metabolites, or standard imaging at very low field entail a challenging tradeoff between resolution, signal-to-noise, and acquisition duration.
Rishabh Sharma +6 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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Sensors, 2021 Although some extended studies about the short-term behavior of NSM FRP strengthened beams have been carried out, there is a lack of knowledge about the behavior of this kind of strengthening under sustained loads and high service temperatures ...
Ricardo Perera +4 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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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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Estimating the impact of environmental management on strawberry yield using publicly available agricultural data in South Korea [PDF]
PeerJ, 2023 Advanced information and communication technologies (ICTs) have made data collection more efficient for agricultural studies. Using publicly available database in South Korea, we estimated the relationship between the management of air temperature and ...
Steven Kim +4 more
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Do quality labels change how much we like a product? Evidence from honey consumers [PDF]
Journal of Central European AgricultureThis study analyses the joint effects of sensory attributes and quality labels on consumer perception and purchase intention of acacia honey on the Croatian market.
Marija CERJAK +3 more
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GIScience & Remote Sensing, 2020 The physical processes associated with the constituents of the troposphere, such as aerosols have an immediate impact on human health. This study employs a novel method to calibrate Aerosol Optical Depth (AOD) obtained from the MODerate resolution ...
S. L. Kesav Unnithan, L. Gnanappazham
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