Results 91 to 100 of about 328,528 (303)
Robust estimation of mean and dispersion functions in extended generalized additive models. [PDF]
Generalized Linear Models are a widely used method to obtain parametric estimates for the mean function. They have been further extended to allow the relationship between the mean function and the covariates to be more flexible via Generalized Additive ...
Croux, Christophe +2 more
core +3 more sources
ABSTRACT Objective Super‐Refractory Status Epilepticus (SRSE) is a rare, life‐threatening neurological emergency with unclear etiology in many cases. Mitochondrial dysfunction, often due to disease‐causing genetic variants, is increasingly recognized as a cause, with each gene producing distinct pathophysiological mechanisms.
Pouria Mohammadi +2 more
wiley +1 more source
Optimal Scaling of Interaction Effects in Generalized Linear Models [PDF]
Multiplicative interaction models, such as Goodman's RC(M) association models, can be a useful tool for analyzing the content of interaction effects. However, most models for interaction effects are only suitable for data sets with two or three predictor
Koning, A.J. +2 more
core +1 more source
ABSTRACT Introduction Spinal cord infarction (SCI) is a rare but devastating myelopathy, characterized by a high disability rate and an unfavorable prognosis. It has often been underdiagnosed and misdiagnosed as idiopathic transverse myelitis (ITM). This study aimed to describe the clinical features, radiological biomarkers, treatments, and functional ...
Zeqiang Ji +13 more
wiley +1 more source
Remote Assessment of Ataxia Severity in SCA3 Across Multiple Centers and Time Points
ABSTRACT Objective Spinocerebellar ataxia type 3 (SCA3) is a genetically defined ataxia. The Scale for Assessment and Rating of Ataxia (SARA) is a clinician‐reported outcome that measures ataxia severity at a single time point. In its standard application, SARA fails to capture short‐term fluctuations, limiting its sensitivity in trials.
Marcus Grobe‐Einsler +20 more
wiley +1 more source
Robust Inference in Generalized Linear Models
Robust inference on the parameters in generalized linear models is performed using the weighted likelihood method. Two cases are considered: a case with replicated observations and a case with a single observation of the dependent variable for each combination of the explanatory variables.
Alqallaf, Fatemah, Agostinelli, Claudio
openaire +3 more sources
Nonparametric estimation of mean and dispersion functions in extended generalized linear models. [PDF]
In this paper the interest is in regression analysis for data that show possibly overdispersion or underdispersion. The starting point for modeling are generalized linear models in which we no longer admit a linear form for the mean regression function ...
Prosdocimi, Ilaria +2 more
core
Clustering Algorithm Reveals Dopamine‐Motor Mismatch in Cognitively Preserved Parkinson's Disease
ABSTRACT Objective To explore the relationship between dopaminergic denervation and motor impairment in two de novo Parkinson's disease (PD) cohorts. Methods n = 249 PD patients from Parkinson's Progression Markers Initiative (PPMI) and n = 84 from an external clinical cohort.
Rachele Malito +14 more
wiley +1 more source
Diagnostics for generalised linear mixed models [PDF]
Generalized linear mixed models are generalized linear models that include random effects varying between clusters or 'higher-level' units of hierarchically structured data. Such models can be estimated using gllamm.
Sophia Rabe-Hesketh, Anders Skrondal
core
ABSTRACT Objective To delineate specific in vivo white matter pathology in neuronal intranuclear inclusion disease (NIID) using diffusion spectrum imaging (DSI) and define its clinical relevance. Methods DSI was performed on 42 NIID patients and 38 matched controls.
Kaiyan Jiang +10 more
wiley +1 more source

