Results 61 to 70 of about 1,154,169 (302)
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
Complementarity of Long‐Reads and Optical Mapping in Parkinson's Disease for Structural Variants
ABSTRACT Objective Long‐read sequencing and optical genome mapping technologies have the ability to detect large and complex structural variants. This has led to the discovery of novel pathogenic variants in neurodegenerative movement disorders. Thus, we aimed to systematically compare the SV detection capabilities of OGM and ONT in Parkinson's disease.
André Fienemann +17 more
wiley +1 more source
An instrumental variable model of multiple discrete choice [PDF]
This paper studies identification of latent utility functions in multiple discrete choice models in which there may be endogenous explanatory variables, that is explanatory variables that are not restricted to be distributed independently of the ...
Adam Rosen +2 more
core +3 more sources
The Identification and Economic Content of Ordered Choice Models with Stochastic Thresholds [PDF]
This paper extends the widely used ordered choice model by introducing stochastic thresholds and interval-specific outcomes. The model can be interpreted as a generalization of the GAFT (MPH) framework for discrete duration data that jointly models ...
Flavio Cunha +2 more
core
ABSTRACT Background Emerging evidence suggests that low‐frequency neural oscillations are dynamically regulated by consciousness levels, with the recovery of low cortical activity potentially serving as a neurophysiological substrate for conscious emergence. Targeted enhancement of these low‐frequency rhythms in patients with disorders of consciousness
Chuan Xu +10 more
wiley +1 more source
Pregibit: A Family of Discrete Choice Models [PDF]
The pregibit discrete choice model is built on a distribution that allows symmetry or asymmetry and thick tails, thin tails or no tails. Thus the model is much richer than the traditional models that are typically used to study behavior that generates ...
Vijverberg, Chu-Ping C. +1 more
core
A Theoretical Foundation for Count Data Models [PDF]
The paper develops a theoretical foundation for using count data models in travel cost analysis. Two micro models are developed: a restricted choice model and a repeated discrete choice model. We show that both models lead to identical welfare measures.
Daniel Hellerstein +3 more
core +8 more sources
Approximating Choice Data by Discrete Choice Models
We obtain a necessary and sufficient condition under which random-coefficient discrete choice models, such as mixed-logit models, are rich enough to approximate any nonparametric random utility models arbitrarily well across choice sets. The condition turns out to be the affine-independence of the set of characteristic vectors. When the condition fails,
Chang, Haoge +2 more
openaire +2 more sources
Objectives There is growing interest in evaluating new strategies to delay or prevent post‐traumatic osteoarthritis (PTOA) in individuals who have sustained anterior cruciate ligament (ACL) injury. This study sought to determine characteristics of potential treatments that are acceptable to patients with ACL injury.
Kevin Kennedy +9 more
wiley +1 more source
Generating Optimal Designs for Discrete Choice Experiments in R: The idefix Package
Discrete choice experiments are widely used in a broad area of research fields to capture the preference structure of respondents. The design of such experiments will determine to a large extent the accuracy with which the preference parameters can be ...
Frits Traets +2 more
doaj +1 more source

