Results 61 to 70 of about 604,873 (258)
Model selection in linear mixed effect models
Journal of Multivariate Analysis, 2012 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Heng Peng, Ying Lu 0005
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Pediatric Blood &Cancer, EarlyView.ABSTRACT Background Animal‐assisted activities (AAAs) with therapy dogs have shown positive effects on patient well‐being and quality of life in various areas of medicine, including pediatric oncology. However, research on this topic is limited. The aim of this study is to present the current status of AAA in pediatric oncology in Germany, Austria, and
Jan‐Marius Wedig +7 more
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, 2021 The best way to understand a linear mixed model, or mixed linear model in some earlier literature, is to first recall a linear regression model. The latter can be expressed as y = Xβ + 𝜖, where y is a vector of observations, X is a matrix of known covariates, β is a vector of unknown regression coefficients, and 𝜖 is a vector of (unobservable random ...
Jiming Jiang, Thuan Nguyen
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Pediatric Blood &Cancer, EarlyView.ABSTRACT Pediatric supportive care clinical trials often involve multiple clinically important outcomes, complicating trial interpretation. Hierarchical composite endpoints (HCEs) provide a framework to integrate key outcomes according to clinical importance.
Willem H. Collier +11 more
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Half-Normal Plots and Overdispersed Models in R: The hnp Package
Journal of Statistical Software, 2017 Count and proportion data may present overdispersion, i.e., greater variability than expected by the Poisson and binomial models, respectively. Different extended generalized linear models that allow for overdispersion may be used to analyze this type of
Rafael A Moral +2 more
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Pediatric Blood &Cancer, EarlyView.ABSTRACT Background Childhood aplastic anemia (AA) is a rare disease, and both the disease itself and its treatment cause significant morbidity. We aimed to determine the contemporary incidence of childhood AA in Finland, to compare the clinical characteristics of AA against inherited bone marrow failure syndromes (IBMFS) and refractory cytopenia of ...
Lauri‐Matti Kulmala +8 more
wiley +1 more source
Revista Colombiana de Estadística, 2007 The mixed linear model is characterized using the classic linear model of Gauss-Markov. The multipliers of Lagrange are a tool to obtain the best lineal predictors (BLUP), we shown the results of Searle (1997), where some sums of the best linear unbiased
López Luis Alberto +2 more
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Determining Parental Factors for Clinical Trial Attrition in Pediatric Acute Lymphoblastic Leukemia
Pediatric Blood &Cancer, EarlyView.ABSTRACT Background/Objectives Despite high enrollment rates on Children's Oncology Group (COG) protocols, attrition after initial consent is challenging, introducing bias and prolonging trial completion. While adult oncology literature has identified predictors of withdrawal, little is known about caregiver decision‐making for child participation in ...
Kimberly L. Stathas +3 more
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Pediatric Blood &Cancer, EarlyView.ABSTRACT Introduction Nephrogenic rests (NRs) and nephroblastomatosis (NBM) are precursor lesions for development of Wilms tumor (WT). Their association with the risk of relapse has not been properly assessed, partly due to misunderstanding of their diagnostic criteria and terminology.
Gordan M. Vujanić +5 more
wiley +1 more source
Sobre la construcción del mejor predictor lineal insesgado (BLUP) y restricciones asociadas
Revista Colombiana de Estadística, 2007 A través del modelo lineal clásico de Gauss-Markov, se caracteriza el modelo de efectos mixtos, se aplica la técnica de multiplicadores de Lagrange para obtener los mejores predictores lineales (BLUP) y se ilustran los resultados de Searle (1997), donde ...
LUIS ALBERTO LÓPEZ +2 more
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