Results 71 to 80 of about 1,921,898 (301)

Military Service Roles and ALS Among Veterans: A Matched Case–Control Study

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT While military service is an established risk factor for amyotrophic lateral sclerosis (ALS), it remains unclear whether this association is linked to combat. We conducted a matched case–control study comparing 191 ALS patients who were veterans of the Israeli Defense Forces (IDF) with known military service type and 1910 matched controls. The
Asaf Honig, Roy Dayan, Amir Knaani, Hagai Levine, Marc Gotkine   +4 more
wiley   +1 more source

Logistic regression against a divergent Bayesian network

Medwave, 2015
This article is a discussion about two statistical tools used for prediction and causality assessment: logistic regression and Bayesian networks. Using data of a simulated example from a study assessing factors that might predict pulmonary emphysema ...
Noel Antonio Sánchez Trujillo
doaj   +1 more source

Influence of Dystrophin Isoform Deficiency on Motor Development in Duchenne Muscular Dystrophy

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective In Duchenne muscular dystrophy (DMD), lack of the shorter dystrophin isoforms Dp140 and Dp71 is associated with increased central nervous system (CNS) involvement. We aimed to investigate how CNS involvement affects motor development in young DMD boys.
Mary Chesshyre, Deborah Ridout, Georgia Stimpson, Laurent Servais, Giovanni Baranello, Adnan Manzur, UK NorthStar Clinical Network, M. Scoto, A. Sarkozy, P. Munot, S. Robb, E. Chan, V. Robinson, W. Girshab, V. Crook, E. Milev, L. Abbott, A. Wolfe, E. O’Reilly, J. Watts‐Whent, N. Burnett, R. Thomas, R. Terespolsky, O. Martinaeu, J. Longatto, V. Straub, C. Bettolo, M. Guglieri, J. Diaz‐Manera, G. Tasca, M. Elseed, R. Muni‐Lofra, M. James, D. Moat, J. Sodhi, K. Wong, E. Robinson, E. Groves, R. Rabb, D. Parasuraman, H. McMurchie, H. Chase, Tracey Willis, C. Rylance, N. Birchall, E. Wright, A. Childs, K. Pysden, C. Martos, D. Roberts, L. Pallant, S. Walker, A. Henderson, R. Madhu, R. Karuvattil, Y. Balla, S. Gregson, S. Clark, E. Wraige, H. Jungbluth, V. Gowda, M. Vanegas, J. Sheehan, A. Schofield, C. Smith, I. Hughes, E. Whitehouse, S. Warner, E. Reading, N. Emery, J. Moustoukas, K. Strachan, M. Ong, M. Atherton, N. Mills, S. Sanchez Marco, A. Saxena, K. Skone, J. TeWaterNaude, H. Davis, C. Wood, A. Majumdar, A. Murugan, I. Guarino, R. Tomlinson, H. Jarvis, L. Wills, C. Frimpong, J. Watson, G. Cobb, G. Robertson, P. Brink, J. Burslem, C. Adams, J. Wong, S. Joseph, I. Horrocks, J. Dunne, M. DiMarco, S. Brown, S. McKenzie, K. Torne, R. Mohamed, V. Velmurugan, M. Prasad, S. Sedehizadeh, A. Schugal, R. Keetley, S. Williamson, K. Payne, E. Dowling, P. Fenty, C. de Goede, A. Parkes, K. Baxter, M. Illingworth, N. Bhangu, S. Geary, J. Palmer, K. Shill, S. Tirupathi, A. Shah, D. O’Donogue, J. McVeigh, J. McFetridge, G. Nicfhirleinn, H. Beattie, T. Leyland, K. Stevenson, N. Hussain, D. Baskaran, Z. Lambat, R. Sullivan, L. Locke, G. Ambegaonkar, D. Krishnakumar, J. Taylor, J. Moores, E. Stephen, J. Tewnion, S. Ramdas, M. Sa, A. Skippen, M. Khries, C. Lilien, H. Ramjattan, F. Taylor, H. English, K. Stewart, F. Flint, E. Bartram, R. Noble, Francesco Muntoni   +152 more
wiley   +1 more source

A Comparison of classification/regression trees and logistic regression in failure models [PDF]

, 2015
The use of non-parametric statistical methods, the development of models geared towards the homogeneous characteristics of corporate sub-populations, and the introduction of non-financial variables, are three main issues analysed in this paper.
Blanco Oliver, Antonio Jesús, Irimia Diéguez, Ana Isabel, Vázquez Cueto, María José   +2 more
core  

Sequence Analysis to Phenotype Health Care Patterns in Adults With Musculoskeletal Conditions Using Primary Care Electronic Health Records

Arthritis Care &Research, EarlyView.
Objective The aim of this study was to apply sequence analysis (SA) to phenotype health care patterns of adult patients with musculoskeletal (MSK) conditions using primary care electronic health records and to investigate the association between these health care patterns and patients’ self‐reported outcomes after consultation.
Smitha Mathew, George Peat, Emma Parry, Ross Wilkie, Kelvin P. Jordan, Jonathan C. Hill, Dahai Yu   +6 more
wiley   +1 more source

Properties of estimators of parameters in logistic regression models [PDF]

, 1985
Properties of various types of estimators of the regression coefficients in linear logistic regression models are considered. The estimators include those based on maximum likelihood, minimum chi-square and weighted least squares.
Al-Sarraf, Z, Young, D H
core  

Common pitfalls in statistical analysis: Logistic regression

Perspectives in Clinical Research, 2017
Logistic regression analysis is a statistical technique to evaluate the relationship between various predictor variables (either categorical or continuous) and an outcome which is binary (dichotomous).
Priya Ranganathan, C S Pramesh, Rakesh Aggarwal   +2 more
doaj   +1 more source

Longitudinal Relationship Between Pain and Depression in People With Inflammatory Arthritis: A Narrative Review

Arthritis Care &Research, EarlyView.
As many patients with inflammatory arthritis (IA) have chronic pain, understanding how to best assess and manage pain in IA is a priority. Comorbid depression is prevalent in adults with IA, affecting 15% to 39% of people. Although pain and depression are thought to be associated in IA, this concept is largely based on cross‐sectional data.
Natasha Cox, Saeed Farooq, Helen Twohig, Ian C. Scott   +3 more
wiley   +1 more source

Model selection in logistic regression

, 2015
This paper is devoted to model selection in logistic regression. We extend the model selection principle introduced by Birg\'e and Massart (2001) to logistic regression model. This selection is done by using penalized maximum likelihood criteria.
Kwemou, Marius, Taupin, Marie-Luce, Tocquet, Anne-Sophie   +2 more
core   +1 more source

Targeting: Logistic Regression, Special Cases and Extensions

ISPRS International Journal of Geo-Information, 2014
Logistic regression is a classical linear model for logit-transformed conditional probabilities of a binary target variable. It recovers the true conditional probabilities if the joint distribution of predictors and the target is of log-linear form ...
Helmut Schaeben
doaj   +1 more source