Results 31 to 40 of about 1,975,816 (285)

Variational approximation for mixtures of linear mixed models

, 2012
Mixtures of linear mixed models (MLMMs) are useful for clustering grouped data and can be estimated by likelihood maximization through the EM algorithm.
Armagan A., Attias H., Booth J.G., Corduneanu A., David J. Nott, Dempster A.P., Meng X.L., Papaspiliopoulos O., Sahu S.K., Scharl T., Siew Li Tan, Verbeek J.J., Wang B., Waterhouse S., Winn J., Wu B., Yeung K.Y., ———   +17 more
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Effect of Conservation Management on Oxisol in a Sugarcane Area Under a Pre-Sprouted Seedling System

Agriculture
Conservation soil management, such as no-tillage and Rip Strip®, can be developed as an alternative to degradation processes such as compaction. This study aimed to compare conventional and conservation soil tillage regarding their soil physical ...
Ingrid Nehmi de Oliveira, Zigomar Menezes de Souza, Denizart Bolonhezi, Rose Luiza Moraes Tavares, Renato Paiva de Lima, Reginaldo Barboza da Silva, Fernando Silva Araújo, Lenon Henrique Lovera, Elizeu de Souza Lima   +8 more
doaj   +1 more source

Using linear mixed models to analyze learning processes within sessions improves detection of treatment effects: An exemplary study of chronometric mental rotation

Methods in Psychology, 2022
Practice effects occur for many cognitive tasks. They are observed not only between repeated tests, but also within sessions. They can confound the detection of treatment effects, even when compared with control groups.
Leonardo Jost, Petra Jansen
doaj   +1 more source

Psychosocial Outcomes in Patients With Endocrine Tumor Syndromes: A Systematic Review

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Introduction The combination of disease manifestations, the familial burden, and varying penetrance of endocrine tumor syndromes (ETSs) is unique. This review aimed to portray and summarize available data on psychosocial outcomes in patients with ETSs and explore gaps and opportunities for future research and care.
Daniël Zwerus, Floortje Strobbe, Annemarie A. Verrijn Stuart, Hanneke M. van Santen, Gerlof D. Valk, Sasja A. Schepers, Rachel S. van Leeuwaarde   +6 more
wiley   +1 more source

Application of an Empirical Best Linear Unbiased Prediction Fay–Herriot (EBLUP-FH) Multivariate Method with Cluster Information to Estimate Average Household Expenditure

Mathematics, 2022
Data at a smaller regional level has now become a necessity for local governments. The average data on household expenditure on food and non-food is designed for provincial and district/city estimation levels.
Armalia Desiyanti, Irlandia Ginanjar, Toni Toharudin   +2 more
doaj   +1 more source

Subset Selection for Linear Mixed Models

Biometrics, 2022
AbstractLinear mixed models (LMMs) are instrumental for regression analysis with structured dependence, such as grouped, clustered, or multilevel data. However, selection among the covariates—while accounting for this structured dependence—remains a challenge. We introduce a Bayesian decision analysis for subset selection with LMMs. Using a Mahalanobis
openaire   +3 more sources

Prognostic Impact of Treatment Modalities, Including Targeted Compartmental Radio‐Immunotherapy, in a Cohort of Neuroblastoma Patients With CNS Metastases at Relapse

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Introduction Neuroblastoma (NB) with central nervous system (CNS) metastases is rare at diagnosis, but occurs more often during relapse/progression. Patients with CNS metastases face a dismal prognosis, with no standardized curative treatment available.
Vicente Santa‐Maria Lopez, Anna Felip‐Badia, Marina Caballero‐Bellon, Nazaret Sanchez‐Sierra, Alicia Castañeda, Moira Garraus, Maite Gorostegui, Margarida Simão‐Rafael, Juan Pablo Muñoz, Marta Perez‐Somarriba, Salvador Mañe, Mariana Cecilia Planells, Sara Perez‐Jaume, Jaume Mora   +13 more
wiley   +1 more source

Multivariate Generalized Linear Mixed Models for Count Data

Austrian Journal of Statistics
Univariate regression models have rich literature for counting data. However, this is not the case for multivariate count data. Therefore, we present the Multivariate Generalized Linear Mixed Models framework that deals with a multivariate set of ...
Guilherme Parreira da Silva, Henrique Aparecido Laureano, Ricardo Rasmussen Petterle, Paulo Justiniano Ribeiro Júnior, Wagner Hugo Bonat   +4 more
doaj   +1 more source

Linear mixed effects models under inequality constraints with applications.

PLoS ONE, 2014
Constraints arise naturally in many scientific experiments/studies such as in, epidemiology, biology, toxicology, etc. and often researchers ignore such information when analyzing their data and use standard methods such as the analysis of variance ...
Laura Farnan, Anastasia Ivanova, Shyamal D Peddada   +2 more
doaj   +1 more source

A Note on the Identifiability of Generalized Linear Mixed Models [PDF]

, 2014
I present here a simple proof that, under general regularity conditions, the standard parametrization of generalized linear mixed model is identifiable.
Labouriau, Rodrigo
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