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Primer on binary logistic regression [PDF]
Family Medicine and Community Health, 2021 Family medicine has traditionally prioritised patient care over research. However, recent recommendations to strengthen family medicine include calls to focus more on research including improving research methods used in the field. Binary logistic regression is one method frequently used in family medicine research to classify, explain or predict the ...
Jenine K Harris
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Endogeneity in Logistic Regression Models
Emerging Infectious Diseases, 2005 To the Editor: Ethelberg et al. (1) report on a study of the determinants of hemolytic uremic syndrome resulting from Shiga toxin–producing Escherichia coli. The dataset is relatively small, and the authors use stepwise logistic regression models to detect small differences.
George Avery +2 more
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Supporting Regularized Logistic Regression Privately and Efficiently [PDF]
PLoS ONE, 2015 As one of the most popular statistical and machine learning models, logistic regression with regularization has found wide adoption in biomedicine, social sciences, information technology, and so on.
Li, Wenfa +3 more
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Fast binary logistic regression. [PDF]
PeerJ Comput SciThis study presents a novel numerical approach that improves the training efficiency of binary logistic regression, a popular statistical model in the machine learning community.
Saran NA, Nar F.
europepmc +3 more sources
Regression Analysis with Scikit-learn (part 2 - Logistic)
The Programming Historian, 2022 This lesson is the second in a two-part lesson focusing on regression analysis. It provides an overview of logistic regression, how to use Python (scikit-learn) to make a logistic regression model, and a discussion of interpreting the results of such ...
Matthew J. Lavin
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Logistic regression applied to natural hazards: rare event logistic regression with replications [PDF]
Natural Hazards and Earth System Sciences, 2012 Statistical analysis of natural hazards needs particular attention, as most of these phenomena are rare events. This study shows that the ordinary rare event logistic regression, as it is now commonly used in geomorphologic studies, does not always lead ...
M. Guns, V. Vanacker
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Evaluating logistic regression and geographically weighted logistic regression models for predicting orange-fleshed sweet potato adoption intention in Benin. [PDF]
Sci RepThe low adoption rate of biofortified crops, like orange-fleshed sweet potatoes (OFSP), by farmers remains a major food security concern. Accurate forecasting models for OFSP adoption intention are essential for breeding and introduction projects.
Ahoudou I +8 more
europepmc +2 more sources
A three-parameter logistic regression model
Statistical Theory and Related Fields, 2021 Dose–response experiments and data analyses are often carried out according to an optimal design under a model assumption. A two-parameter logistic model is often used because of its nice mathematical properties and plausible stochastic response ...
Xiaoli Yu, Shaoting Li, Jiahua Chen
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Bank Failure Prediction With Logistic Regression [PDF]
International Journal of Economics and Financial Issues, 2013 In recent years the economic and financial world is shaken by a wave of financial crisis and resulted in violent bank fairly huge losses. Several authors have focused on the study of the crises in order to develop an early warning model.
Taha Zaghdoudi
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Logistic regression: A simple primer
Cancer Research, Statistics, and Treatment, 2021 Logistic regression is used to obtain the odds ratio in the presence of more than one explanatory variable. This procedure is quite similar to multiple linear regression, with the only exception that the response variable is binomial.
Ankita Pal
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