Stochastic Expectation Maximization Algorithm for Linear Mixed-Effects Model with Interactions in the Presence of Incomplete Data

The purpose of this paper is to propose a new algorithm based on stochastic expectation maximization (SEM) to deal with the problem of unobserved values when multiple interactions in a linear mixed-effects model (LMEM) are present. We test the effectiveness of the proposed algorithm with the stochas...

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Main Authors: Alandra Zakkour, Cyril Perret, Yousri Slaoui
Format: Article
Language:English
Published: MDPI AG 2023-03-01
Series:Entropy
Subjects:
Online Access:https://www.mdpi.com/1099-4300/25/3/473
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author Alandra Zakkour
Cyril Perret
Yousri Slaoui
author_facet Alandra Zakkour
Cyril Perret
Yousri Slaoui
author_sort Alandra Zakkour
collection DOAJ
description The purpose of this paper is to propose a new algorithm based on stochastic expectation maximization (SEM) to deal with the problem of unobserved values when multiple interactions in a linear mixed-effects model (LMEM) are present. We test the effectiveness of the proposed algorithm with the stochastic approximation expectation maximization (SAEM) and Monte Carlo Markov chain (MCMC) algorithms. This comparison is implemented to highlight the importance of including the maximum effects that can affect the model. The applications are made on both simulated psychological and real data. The findings demonstrate that our proposed SEM algorithm is highly preferable to the other competitor algorithms.
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spelling doaj.art-119baa953cb849d5a65218286085a41b2023-11-17T10:56:41ZengMDPI AGEntropy1099-43002023-03-0125347310.3390/e25030473Stochastic Expectation Maximization Algorithm for Linear Mixed-Effects Model with Interactions in the Presence of Incomplete DataAlandra Zakkour0Cyril Perret1Yousri Slaoui2Laboratoire de Mathématiques et Applications, Université de Poitiers, 11 Boulevard Marie et Pierre Curie, 86962 Futuroscope Chasseneuil, CEDEX 9, 86073 Poitiers, FranceLaboratoire de Mathématiques et Applications, Université de Poitiers, 11 Boulevard Marie et Pierre Curie, 86962 Futuroscope Chasseneuil, CEDEX 9, 86073 Poitiers, FranceLaboratoire de Mathématiques et Applications, Université de Poitiers, 11 Boulevard Marie et Pierre Curie, 86962 Futuroscope Chasseneuil, CEDEX 9, 86073 Poitiers, FranceThe purpose of this paper is to propose a new algorithm based on stochastic expectation maximization (SEM) to deal with the problem of unobserved values when multiple interactions in a linear mixed-effects model (LMEM) are present. We test the effectiveness of the proposed algorithm with the stochastic approximation expectation maximization (SAEM) and Monte Carlo Markov chain (MCMC) algorithms. This comparison is implemented to highlight the importance of including the maximum effects that can affect the model. The applications are made on both simulated psychological and real data. The findings demonstrate that our proposed SEM algorithm is highly preferable to the other competitor algorithms.https://www.mdpi.com/1099-4300/25/3/473linear mixed-effects modelinteractionsmissing datacensored data<tt>EM</tt> algorithm<tt>SEM</tt> algorithm
spellingShingle Alandra Zakkour
Cyril Perret
Yousri Slaoui
Stochastic Expectation Maximization Algorithm for Linear Mixed-Effects Model with Interactions in the Presence of Incomplete Data
Entropy
linear mixed-effects model
interactions
missing data
censored data
<tt>EM</tt> algorithm
<tt>SEM</tt> algorithm
title Stochastic Expectation Maximization Algorithm for Linear Mixed-Effects Model with Interactions in the Presence of Incomplete Data
title_full Stochastic Expectation Maximization Algorithm for Linear Mixed-Effects Model with Interactions in the Presence of Incomplete Data
title_fullStr Stochastic Expectation Maximization Algorithm for Linear Mixed-Effects Model with Interactions in the Presence of Incomplete Data
title_full_unstemmed Stochastic Expectation Maximization Algorithm for Linear Mixed-Effects Model with Interactions in the Presence of Incomplete Data
title_short Stochastic Expectation Maximization Algorithm for Linear Mixed-Effects Model with Interactions in the Presence of Incomplete Data
title_sort stochastic expectation maximization algorithm for linear mixed effects model with interactions in the presence of incomplete data
topic linear mixed-effects model
interactions
missing data
censored data
<tt>EM</tt> algorithm
<tt>SEM</tt> algorithm
url https://www.mdpi.com/1099-4300/25/3/473
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