Results 41 to 50 of about 604,878 (242)
mplot: An R Package for Graphical Model Stability and Variable Selection Procedures
The mplot package provides an easy to use implementation of model stability and variable inclusion plots (Müller and Welsh 2010; Murray, Heritier, and Müller 2013) as well as the adaptive fence (Jiang, Rao, Gu, and Nguyen 2008; Jiang, Nguyen, and Rao ...
Garth Tarr +2 more
doaj +1 more source
ASSIST: Refinement of a Benefits Navigator Intervention Among Low‐Income Pediatric Oncology Families
ABSTRACT Background/Objectives Children with cancer living in poverty experience worse survival and quality of life. Interventions connecting low‐income families to benefits (e.g., Supplemental Nutrition Assistance Program [SNAP] improve health outcomes; yet nearly 50% of SNAP‐eligible pediatric oncology families are unenrolled.
Puja J. Umaretiya +11 more
wiley +1 more source
Non-linear Mixed Models in a Dose Response Modelling
Study designs in which an outcome is measured more than once from time to time result in longitudinal data. Most of the methodological works have been done in the setting of linear and generalized linear models, where some amount of linearity is retained.
Madona Yunita Wijaya
doaj +1 more source
Bayesian Boosting for Linear Mixed Models
Boosting methods are widely used in statistical learning to deal with high-dimensional data due to their variable selection feature. However, those methods lack straightforward ways to construct estimators for the precision of the parameters such as variance or confidence interval, which can be achieved by conventional statistical methods like Bayesian
Boyao Zhang +4 more
openaire +2 more sources
ABSTRACT Background Acute lymphoblastic leukaemia (ALL) is one of the most treatable forms of paediatric cancer; however, there is a substantial burden of treatment‐related toxicities (TRTs). In addition, the long‐term changes in children's health‐related quality of life (HRQoL) due to toxic treatments are not well understood.
Clare Ghows +19 more
wiley +1 more source
Penalized Composite Likelihood Estimation for Spatial Generalized Linear Mixed Models [PDF]
When discussing non-Gaussian spatially correlated variables, generalized linear mixed models have enough flexibility for modeling various data types. However, the maximum likelihood methods are plagued with substantial calculations for large data sets ...
Mohsen Mohammadzadeh, Leyla Salehi
doaj +1 more source
Solid Pseudopapillary Neoplasm of the Pancreas in Children and Adolescents: Expert Recommendations
ABSTRACT Solid pseudopapillary neoplasm of the pancreas (SPN) is a rare low‐grade malignant exocrine pancreatic tumor, mostly discovered during the second decade of life in females, with a very good prognosis, provided microscopically complete surgical excision is achieved.
Sabine Irtan +18 more
wiley +1 more source
lmerSeq: an R package for analyzing transformed RNA-Seq data with linear mixed effects models
Background Studies that utilize RNA Sequencing (RNA-Seq) in conjunction with designs that introduce dependence between observations (e.g. longitudinal sampling) require specialized analysis tools to accommodate this additional complexity.
Brian E. Vestal +2 more
doaj +1 more source
Bayesian Model Selection for Generalized Linear Mixed Models
AbstractWe propose a Bayesian model selection approach for generalized linear mixed models (GLMMs). We consider covariance structures for the random effects that are widely used in areas such as longitudinal studies, genome-wide association studies, and spatial statistics.
Shuangshuang Xu +3 more
openaire +3 more sources
ABSTRACT Neuroblastoma's complex, heterogeneous biology poses significant diagnostic and therapeutic challenges, often requiring caregivers to absorb complex information and participate in time‐sensitive decisions. However, caregivers often feel unprepared to evaluate options.
Vickie Buenger +8 more
wiley +1 more source

