Results 101 to 110 of about 4,991,757 (343)

Logistic Regression [PDF]

Circulation, 2008
  +5 more sources

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

Regression Modeling Strategies with Applications to Linear Models, Logistic and Ordinal Regression and Survival Analysis (2nd Edition)

, 2016
Regression Modeling Strategies is an advanced text, aimed at graduate students and re-searchers with a solid, comprehensive background in regression modeling. Readers should have a good working knowledge of regression analysis as well as R as all code is
James E. Helmreich
semanticscholar   +1 more source

Post‐COVID Fatigue Is Associated With Reduced Cortical Thickness After Hospitalization

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Neuropsychiatric symptoms are among the most prevalent sequelae of COVID‐19, particularly among hospitalized patients. Recent research has identified volumetric brain changes associated with COVID‐19. However, it currently remains poorly understood how brain changes relate to post‐COVID fatigue and cognitive deficits.
Tim J. Hartung, Florentin Steigerwald, Amy Romanello, Cathrin Kodde, Matthias Endres, Sandra Frank, Peter Heuschmann, Philipp Koehler, Stephan Krohn, Daniel Pape, Jens Schaller, Sophia Stöcklein, Istvan Vadasz, Janne Vehreschild, Martin Witzenrath, Thomas Zoller, Carsten Finke, on behalf of the NAPKON Study Group, Y. Ahlgrimm, C. Finke, J. Fricke, T. Keil, L. Krist, N. Lisewsky, M. Mittermaier, M. Mueller‐Plathe, C. Pley, S. Schmidt, A. Stege, F. Steinbeis, S. Steinbrecher, C. Wildberg, M. Witzenrath, E. Zessin, T. Zoller, C. Arendt, C. Bellinghausen, S. Cremer, A. Groh, A. Gruenewaldt, Y. Khodamoradi, S. Klinsing, G. Rohde, M. Vehreschild, T. Vogl, S. Frank, J. C. Hellmuth, M. Huber, S. Kaeaeb, O. T. Keppler, E. Khatamzas, C. Mandel, S. Mueller, M. Muenchhoff, L. Reeh, C. Scherer, H. Stubbe, M. von Bergwelt, L. Weiss, B. Zwissler, S. Cleef, M. E. Figuera Basso, J. Franzenburg, K. Franzpoetter, A. Friedrichs, A. Hermes, J. Heyckendorf, C. Kujat, I. Lehmann, C. Maetzler, S. Meier, D. Pape, S. Poick, L. Reinke, A. K. Russ, A. M. Scheer, D. Schunk, T. Tamminga, S. Bohnet, D. Droemann, K. F. Franzen, R. Hoerster, N. Kaeding, M. Nissen, P. Parschke, J. Rupp, S. Caesar, H. Einsele, S. Frantz, A. Frey, A. Grau, K. Haas, C. Haertel, K. G. Haeusler, G. Hein, J. Herrmann, A. Horn, R. Jahns, P. Meybohm, F. A. Montellano, C. Morbach, J. Schmidt, P. Schulze, S. Stoerk, J. Volkmann, T. Bahmer, A. Hermes, M. Krawczak, W. Lieb, S. Schreiber, T. Tamminga, B. Balzuweit, S. Berger, J. Fricke, M. Hummel, A. Krannich, L. Krist, F. Kurth, J. Lienau, R. Lorbeer, C. Pley, J. Schaller, S. Schmidt, C. Thibeault, M. Witzenrath, T. Zoller, I. Bernemann, T. Illig, M. Kersting, N. Klopp, V. Kopfnagel, S. Muecke, M. Kraus, B. Lorenz‐Depiereux, G. Anton, A. Kuehn‐Steven, S. Kunze, M. K. Tauchert, K. Appel, M. Brechtel, I. Broehl, K. Fiedler, R. Geisler, S. M. Hopff, K. Knaub, C. Lee, S. Nunes de Miranda, S. Raquib, G. Sauer, M. Scherer, J. J. Vehreschild, P. Wagner, L. Wolf, J. C. Hellmuth, K. Guenther, F. Haug, J. Haug, A. Horn, M. Kohls, C. Fiessler, P. U. Heuschmann, O. Miljukov, C. Nuernberger, J. P. Reese, L. Schmidbauer, I. Chaplinskaya, S. Hanss, D. Krefting, C. Pape, M. Rainers, A. Schoneberg, N. Weinert, T. Bahls, W. Hoffmann, M. Nauck, C. Schaefer, M. Schattschneider, D. Stahl, H. Valentin, P. Heuschmann, A. L. Hofmann, S. Jiru‐Hillmann, J. P. Reese, S. Herold, P. Heuschmann, R. Heyder, W. Hoffmann, T. Illig, S. Schreiber, J. J. Vehreschild, M. Witzenrath   +190 more
wiley   +1 more source

Variational Bayesian inference for linear and logistic regression

, 2019
The article describe the model, derivation, and implementation of variational Bayesian inference for linear and logistic regression, both with and without automatic relevance determination.
Drugowitsch, Jan
core  

Sample Size Guidelines for Logistic Regression from Observational Studies with Large Population: Emphasis on the Accuracy Between Statistics and Parameters Based on Real Life Clinical Data

Malaysian Journal of Medical Sciences, 2018
Background Different study designs and population size may require different sample size for logistic regression. This study aims to propose sample size guidelines for logistic regression based on observational studies with large population.
M. Bujang, Nadiah Sa’at, Tg Mohd Ikhwan Tg Abu Bakar Sidik, Lim Chien Joo   +3 more
semanticscholar   +1 more source

Association of Corticospinal Tract Asymmetry With Ambulatory Ability After Intracerebral Hemorrhage

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background Ambulatory ability after intracerebral hemorrhage (ICH) is important to patients. We tested whether asymmetry between ipsi‐ and contra‐lesional corticospinal tracts (CSTs) assessed by diffusion tensor imaging (DTI) is associated with post‐ICH ambulation.
Yasmin N. Aziz, Carl D. Langefeld, Mary E. Comeau, Miranda C. Marion, Tyler P. Behymer, Lee A. Gilkerson, Padmini Sekar, Weihong Yuan, Vivek Khandwala, Brady J. Williamson, Thomas Maloney, Achala Vagal, Pierce Boyne, Kari Dunning, Matthew L. Flaherty, Steven J. Kittner, Prachi Mehndiratta, Gunjan Y. Parikh, Michael L. James, David Roh, Fernando D. Testai, Farhaan S. Vahidy, James Thornton, Ranjit Bagga, Daniel Woo, Stacie L. Demel   +25 more
wiley   +1 more source

Multiple-Trait Mapping of Quantitative Trait Loci After Selective Genotyping Using Logistic Regression [PDF]

, 1999
John Henshall, Michael E. Goddard
openalex   +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

Secure and Differentially Private Logistic Regression for Horizontally Distributed Data [PDF]

, 2019
Miran Kim, Junghye Lee, Lucila Ohno‐Machado, Xiaoqian Jiang   +3 more
openalex   +1 more source