Results 31 to 40 of about 24,944,440 (302)
A mixed model approach for structured hazard regression [PDF]
, 2004 The classical Cox proportional hazards model is a benchmark approach to analyze continuous survival times in the presence of covariate information. In a number of applications, there is a need to relax one or more of its inherent assumptions, such as ...
Thomas Kneib +4 more
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An Introduction to Linear Mixed-Effects Modeling in R [PDF]
Advances in Methods and Practices in Psychological Science, 2020 This Tutorial serves as both an approachable theoretical introduction to mixed-effects modeling and a practical introduction to how to implement mixed-effects models in R. The intended audience is researchers who have some basic statistical knowledge, but little or no experience implementing mixed-effects models in R using their own data. In an attempt
openaire +2 more sources
FishesThis study aims to explore the spatial distribution of false kelpfish (Sebastiscus marmoratus) in the mussel farming area, artificial reef areas of Gouqi Island (Shengsi, China), and natural areas using eDNA detection methods.
Rijin Jiang +6 more
doaj +1 more source
Mixed effect models in distance sampling [PDF]
, 2013 Recently, much effort has been expended for improving conventional distance sampling methods, e.g. by replacing the design-based approach with a model-based approach where observed counts are related to environmental covariates (Hedley and Buckland, 2004)
Oedekoven, Cornelia Sabrina
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Linear mixed models for series of variety trials [PDF]
, 2011 When using linear mixed models for analysis of series of variety trials, the statistical inference space is dependent on the design of the series. In this paper, four inference spaces are recognized for one-year crop variety trials: single-year local ...
Forkman, Johannes
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Permutation Tests for Random Effects in Linear Mixed Models [PDF]
Biometrics, 2011 Summary Inference regarding the inclusion or exclusion of random effects in linear mixed models is challenging because the variance components are located on the boundary of their parameter space under the usual null hypothesis. As a result, the asymptotic null distribution of the Wald, score, and likelihood ratio tests will not have the typical χ2 ...
Lee, Oliver E., Braun, Thomas M.
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A variance shift model for detection of outliers in the linear mixed model
, 2010 A variance shift outlier model (VSOM), previously used for detecting outliers in the linear model, is extended to the variance components model.
Gogel, B. J. +6 more
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Epidemiology, Biostatistics and Public Health, 2018 Background: Randomised controlled trials (RCTs) are the gold standard to estimate treatment effects. When patients receive effective treatment over time they may reach the limit of a certain measurement scale.
Jos Twisk +7 more
doaj +1 more source
A note on conditional AIC for linear mixed-effects models [PDF]
Biometrika, 2008 The conventional model selection criterion AIC has been applied to choose candidate models in mixed-effects models by the consideration of marginal likelihood. Vaida and Blanchard (2005) demonstrated that such a marginal AIC and its small sample correction are inappropriate when the research focus is on clusters.
Hua Liang, Hulin Wu, Guohua Zou
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Pediatric Blood &Cancer, EarlyView.ABSTRACT As part of the European Cooperative Study Group for Paediatric Rare Tumours initiative, we developed standard clinical practice guidelines for ovarian sex cord stromal tumors, based on comprehensive national and international cohort analyses, literature review, and a final expert consensus conference.
Dominik T. Schneider +15 more
wiley +1 more source