Results 31 to 40 of about 3,064,284 (141)
, 2011 Nonlinear mixed effects models represent a powerful tool to simultaneously analyze data from several individuals. In this study a compartmental model of leucine kinetics is examined and extended with a stochastic differential equation to model non-steady
Adiels, Martin +4 more
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Novel Modelling Approaches to Characterize and Quantify Carryover Effects on Sensory Acceptability
Foods, 2018 Sensory biases caused by the residual sensations of previously served samples are known as carryover effects (COE). Contrast and convergence effects are the two possible outcomes of carryover.
Damir Dennis Torrico +5 more
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Bayesian P-Splines to investigate the impact of covariates on Multiple Sclerosis clinical course [PDF]
, 2003 This paper aims at proposing suitable statistical tools to address heterogeneity in repeated measures, within a Multiple Sclerosis (MS) longitudinal study.
Di Serio, C., Lamina, C.
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D-optimal designs formulti-response linear mixed models [PDF]
, 2018 Linear mixed models have become popular in many statistical applications duringrecent years. However design issues for multi-response linear mixed models are rarelydiscussed.
Liu, Xin, Wong, Weng Kee, Yue, Rong-Xian
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Generalized score test of homogeneity for mixed effects models
, 2006 Many important problems in psychology and biomedical studies require testing for overdispersion, correlation and heterogeneity in mixed effects and latent variable models, and score tests are particularly useful for this purpose. But the existing testing
Zhang, Heping, Zhu, Hongtu
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A note on Influence diagnostics in nonlinear mixed-effects elliptical models
, 2009 This paper provides general matrix formulas for computing the score function, the (expected and observed) Fisher information and the $\Delta$ matrices (required for the assessment of local influence) for a quite general model which includes the one ...
Alexandre G. Patriota +13 more
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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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influence.ME: tools for detecting influential data in mixed effects models [PDF]
, 2011 influence.ME provides tools for detecting influential data in mixed effects models. The application of these models has become common practice, but the development of diagnostic tools has lagged behind.
Grotenhuis, M. te +2 more
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The relative efficiency of time-to-progression and continuous measures of cognition in presymptomatic Alzheimer's disease. [PDF]
, 2019 IntroductionClinical trials on preclinical Alzheimer's disease are challenging because of the slow rate of disease progression. We use a simulation study to demonstrate that models of repeated cognitive assessments detect treatment effects more ...
Aisen, Paul S +4 more
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Fitting Linear Mixed-Effects Models Using lme4
Journal of Statistical Software, 2015 Maximum likelihood or restricted maximum likelihood (REML) estimates of the parameters in linear mixed-effects models can be determined using the lmer function in the lme4 package for R. As for most model-fitting functions in R, the model is described in
Douglas Bates +3 more
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