Results 121 to 130 of about 397,901 (297)
Log-linear models for ordinal data. Some examples
, 2004 The paper presents an analysis of association in a contingency table using log-linear models. The focus is made on situation when at least one of variables is measured on an ordinal scale.
Przybysz, Dariusz
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Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Background X‐linked adrenoleukodystrophy (X‐ALD) is a neurometabolic disorder caused by pathogenic variants in ABCD1, leading to slowly progressive spinal cord disease in nearly all affected men. Sensitive biomarkers to quantify disease severity and predict progression are needed for clinical care and trial design.
Eda G. Kabak +4 more
wiley +1 more source
Log-linear models with dependent spatial data
Log-linear models are an appropriate means of determining the magnitude and direction of interactions between categorical variables that in common with other statistical models assume independent observations. Spatial data are often dependent rather than
B Fingleton
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, 1978 This thesis is concerned with the effect of classification error on contingency tables being analyzed with hierarchical log-linear models (independence in an I x J table is a particular hierarchical log-linear model).
Korn, E L
core +1 more source
Predictive Ability of Plasma p‐tau217 for β‐Amyloid Status: A Prospective Multicenter Study
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Plasma tau phosphorylated at threonine 217 (p‐tau217) measured with fully automated platforms has shown high accuracy for Alzheimer's disease (AD) diagnosis, but real‐world multicenter data remain limited. We aimed to validate the diagnostic performance of p‐tau217 for identifying AD pathology in a real‐world multicenter cohort ...
Miquel Massons +33 more
wiley +1 more source
Log-linear models of petroleum product demand : an international study [PDF]
, 1978 The purpose of this work is to describe a set of log-linear models of petroleum product demand and to document the estimation results. This effort is part of an overall study to understand and model the world oil market.
Ross J. Heide, Heide, Ross J.
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Log-linear Models and Closed Form Estimates for Missing Values in Two Dimensional Contingency Tables
Cumhuriyet Science JournalThe problem of missing data is frequently encountered in scientific research due to various reasons such as nonresponse in surveys, data recording errors, data loss, or limitations inherent in the study design. Missing data mechanisms are classified into
Emine Öçal +1 more
doaj +1 more source
LOG‐LINEAR MODELLING OF SPATIAL INTERACTION
Papers in Regional Science, 1983 The research reported in this paper is part of a larger research effort to develop a methodology for estimating spatial interaction (migration) flows. The first section of the paper summarises the equivalences between the log-linear model and conventional spatial interaction models.
openaire +1 more source
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective To evaluate the efficacy and safety of ofatumumab in patients with myelin oligodendrocyte glycoprotein antibody–associated disease (MOGAD), and compare it with rituximab. Methods We conducted a single–center, observational study including 22 MOGAD patients treated with ofatumumab and 21 treated with rituximab.
Yuxin Fan +5 more
wiley +1 more source
Question Classification with Log-Linear Models
, 2008 Question classification has become a crucial step in modern question answering systems. Previous work has demonstrated the effectiveness of statistical machine learning approaches to this problem. This paper presents a new approach to building a question
Phil Blunsom
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