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Diagnostic Histopathology, ISSN 1756-2317, 2016, Volume 22, Issue 7, pp. 271 - 278
Abstract Regression models are widely used for addressing scientific questions of interest regarding the associations among a set of variables... 
Pathology | generalized linear models | interaction | linear regression | prediction | confounding | logistic regression
Journal Article
2000, 2nd ed., Wiley series in probability and statistics, ISBN 9780471356325, 397
From the reviews of the First Edition.'An interesting, useful, and well-written book on logistic regression models... 
Regression analysis | Statistics | Mathematics
eBook
2008, 2nd ed., ISBN 9780471754992, xiii, 392
.... Applied Survival Analysis, Second Edition provides a comprehensive and up-to-date introduction to regression modeling for time-to-event data in medical, epidemiological, biostatistical... 
Medicine | Prognosis | Logistic Models | Data processing | Statistical methods | Medical sciences | Research | Regression analysis | Mathematical Computing | Logistic distribution | Computer programs
Book
2002, 2nd ed., Statistics for biology and health., ISBN 0387953973, xiv, 513
Book
Neural computation, ISSN 1530-888X, 2007, Volume 19, Issue 3, pp. 792 - 815
In this letter, we propose two new support vector approaches for ordinal regression, which optimize multiple thresholds to define parallel discriminant hyperplanes for the ordinal scales... 
NEUROSCIENCES | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | SMO ALGORITHM | Algorithms | Artificial Intelligence | Humans | Information Storage and Retrieval | Weights and Measures | Logistic Models | Pattern Recognition, Automated - methods | Discriminant Analysis
Journal Article
The Annals of statistics, ISSN 0090-5364, 2010, Volume 38, Issue 3, pp. 1287 - 1319
.... We describe a method based on ℓ₁-regularized logistic regression, in which the neighborhood of any given node is estimated by performing logistic regression subject to an ℓ₁-constraint... 
Logistic regression | Sample size | Machine learning | Ising model | Markov models | Modeling | Consistent estimators | Vertices | Fisher information | Estimation methods | ℓ1-regularization | Graphical models | Structure learning | Model selection | High-dimensional asymptotics | Convex risk minimization | Markov random fields | 68T99 | convex risk minimization | high-dimensional asymptotics | model selection | 62F12 | structure learning | ℓ_1-regularization
Journal Article
Canadian Medical Association journal (CMAJ), ISSN 1488-2329, 2011, Volume 184, Issue 8, pp. 895 - 899
Logistic regression analysis, which estimates odds ratios, is often used to adjust for covariables in cohort studies and randomized controlled trials (RCTs... 
MEDICINE, GENERAL & INTERNAL | COMMON OUTCOMES | RARE-DISEASE ASSUMPTION | RELATIVE RISK | ESTIMATORS | Logistic Models | Data Interpretation, Statistical | Odds Ratio | Randomized Controlled Trials as Topic - methods | Humans | Cohort Studies | Clinical trials | Logistic regression | Methods | Studies | Regression analysis | Risk assessment | Analysis
Journal Article
Journal Article