Results 41 to 50 of about 819,272 (292)
Over the past several decades, ecologists have been striving to develop models that accurately describe species-habitat relationships across ecological communities.
Rubina Mondal, Anuradha Bhat
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Minimization of Akaike's information criterion in linear regression analysis via mixed integer nonlinear program [PDF]
Akaike's information criterion (AIC) is a measure of evaluating statistical models for a given data set. We can determine the best statistical model for a particular data set by finding the model with the smallest AIC value. Since there are exponentially
K. Kimura, Hayato Waki
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Epigenome-wide association studies seek to identify DNA methylation sites associated with clinical outcomes. Difference in observed methylation between specific cell-subtypes is often of interest; however, available samples often comprise a mixture of ...
Daniel W Kennedy +8 more
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Bayesian multimodel inference for geostatistical regression models. [PDF]
The problem of simultaneous covariate selection and parameter inference for spatial regression models is considered. Previous research has shown that failure to take spatial correlation into account can influence the outcome of standard model selection ...
Devin S Johnson, Jennifer A Hoeting
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Summary OBJECTIVES The emergence of big cardio-thoracic surgery datasets that include not only short-term and long-term discrete outcomes but also repeated measurements over time offers the opportunity to apply more advanced modelling of outcomes.
Xu Wang +4 more
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Selection practices are maximized when plant breeders have the availability of consolidated parameters, which will guide direct and indirect selection methods.
Ivan Ricardo Carvalho +5 more
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Variational Bayesian EM Algorithm for Quantile Regression in Linear Mixed Effects Models
This paper extends the normal-beta prime (NBP) prior to Bayesian quantile regression in linear mixed effects models and conducts Bayesian variable selection for the fixed effects of the model.
Weixian Wang, Maozai Tian
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A comparison of multiple imputation methods for missing data in longitudinal studies
Background Multiple imputation (MI) is now widely used to handle missing data in longitudinal studies. Several MI techniques have been proposed to impute incomplete longitudinal covariates, including standard fully conditional specification (FCS-Standard)
Md Hamidul Huque +3 more
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A mixed-effects model for growth curves analysis in a two-way crossed classification layout
We propose a mixed-effects linear model for analyzing growth curves data obtained using a two-way classification experiment. The model combines an unconstrained means model and a regression model on the time, in which the coefficients are considered ...
Mario Miguel Ojeda, Hardeo Sahai
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ABSTRACT Background Pediatric bone sarcoma patients and survivors may experience psychosocial challenges related to childhood cancer after their intensive, body‐altering treatment. This cross‐sectional study aimed to evaluate generic and survivor‐specific psychosocial outcomes in a national cohort of pediatric bone sarcoma patients and survivors, and ...
Hinke van der Hoek +14 more
wiley +1 more source

