Results 101 to 110 of about 1,513,668 (313)
Model Selection in Linear Mixed Models
Statistical Science, 2013 Linear mixed effects models are highly flexible in handling a broad range of data types and are therefore widely used in applications. A key part in the analysis of data is model selection, which often aims to choose a parsimonious model with other desirable properties from a possibly very large set of candidate statistical models.
Müller, Samuel +2 more
openaire +4 more sources
FEBS Letters, EarlyView.We present robust protocols for the preparation of supported lipid bilayers (SLBs) incorporating either Salmonella smooth LPS or outer membrane vesicles (OMVs). We use a combination of quartz crystal microbalance with dissipation (QCM‐D) and fluorescence microscopy to both characterize the SLBs of various compositions and to probe their interactions ...
Hudson P. Pace +6 more
wiley +1 more source
Smooth-car mixed models for spatial count data [PDF]
Penalized splines (P-splines) and individual random effects are used for the analysis of spatial count data. P-splines are represented as mixed models to give a unified approach to the model estimation procedure.
Dae-Jin Lee, Maria Durban
core
FEBS Letters, EarlyView.Proteostasis and the gut microbiota play a key role in shaping host physiology. Microbiota‐derived metabolites, vitamins, and RNA modulate host proteostasis. Findings from model systems, including C. elegans, indicate microbes can either stabilize or disrupt host proteostasis.
Abhishek Anil Dubey, Maria Ermolaeva
wiley +1 more source
Mixed effect models in distance sampling
, 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
core
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 +3 more
core +1 more source
Bayesian Option Pricing Using Mixed Normal Heteroskedasticity Models [PDF]
While stochastic volatility models improve on the option pricing error when compared to the Black-Scholes-Merton model, mispricings remain. This paper uses mixed normal heteroskedasticity models to price options. Our model allows for significant negative
Jeroen V.K. Rombouts, Lars Stentoft
core +2 more sources
Frontiers in Psychology, 2014 The association between socioeconomic status and child cognitive development, and the positive impact of interventions aimed at optimizing cognitive performance, are well documented.
María Soledad eSegretin +6 more
doaj +1 more source
FEBS Letters, EarlyView.Inositol pyrophosphates are energy‐rich signaling molecules that perform critical functions in cells. Three different families of phosphatases hydrolyze the β phosphate of the inositol pyrophosphate molecules: two have narrow specificities and one is promiscuous.
Ronda J. Rolfes
wiley +1 more source