Results 31 to 40 of about 489,917 (280)
Generalized degrees of freedom and adaptive model selection in linear mixed-effects models [PDF]
Computational Statistics & Data Analysis, 2011 Linear mixed-effects models involve fixed effects, random effects and covariance structure, which require model selection to simplify a model and to enhance its interpretability and predictability. In this article, we develop, in the context of linear mixed-effects models, the generalized degrees of freedom and an adaptive model selection procedure ...
Zhang, Bo +2 more
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Factors Affecting Contraceptive Use in Ethiopian: A Generalized Linear Mixed Effect Model
Ethiopian Journal of Health Sciences, 2021 BACKGROUND: Ethiopia is the second most populous nations in Africa. Family planning is a viable solution to control such fast-growing population. This study aimed to assess the prevalence of contraceptive use and its predictors in Ethiopia.METHODS: About 4,563 women were drawn randomly by Central Statistics Agency from its master sampling frame.
Mulusew Admassu, Awoke Seyoum Tegegne
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Penalized additive regression for space-time data: a Bayesian perspective [PDF]
, 2003 We propose extensions of penalized spline generalized additive models for analysing space-time regression data and study them from a Bayesian perspective.
Fahrmeir, Ludwig +2 more
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Generalized partially linear mixed-effects models incorporating mismeasured covariates [PDF]
Annals of the Institute of Statistical Mathematics, 2007 In this article we consider a semiparametric generalized mixed-effects model, and propose combining local linear regression, and penalized quasilikelihood and local quasilikelihood techniques to estimate both population and individual parameters and nonparametric curves.
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Scale and Sensitivity of Songbird Occurrence to Landscape Structure in a Harvested Boreal Forest
Avian Conservation and Ecology, 2005 To explore the spatial scales at which boreal forest birds respond to landscape structure and how those responses are influenced by forest harvest, we quantified the relationship between amounts of forest in the landscape at multiple spatial scales and ...
Philip D. Taylor, Meg A. Krawchuk
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, 2020 Recently, applied sciences, including longitudinal and clustered studies in biomedicine require the analysis of ultra-high dimensional linear mixed effects models where we need to select important fixed effect variables from a vast pool of available ...
Ghosh, Abhik, Thoresen, Magne
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Multivariate Survival Mixed Models for Genetic Analysis of Longevity Traits [PDF]
, 2014 A class of multivariate mixed survival models for continuous and discrete time with a complex covariance structure is introduced in a context of quantitative genetic applications.
Labouriau, Rodrigo +2 more
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PLoS ONE, 2021 Binary Generalized Linear Mixed Model (GLMM) is the most common method used by researchers to analyze clustered binary data in biological and social sciences.
Chénangnon Frédéric Tovissodé +2 more
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Statistical model assumptions achieved by linear models: classics and generalized mixed
Revista Ciência Agronômica, 2020 When an agricultural experiment is completed and the data about the response variable is available, it is necessary to perform an analysis of variance.
Rita Carolina de Melo +4 more
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Generalized semiparametrically structured mixed models [PDF]
, 2001 Generalized linear mixed models are a common tool in statistics which extends generalized linear models to situations where data are hierarchically clustered or correlated.
Tutz, Gerhard
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