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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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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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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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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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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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Loan classification using logistic regression
Informatika, 2023 Objectives. The studied problem of loan classification is particularly important for financial institutions, which must efficiently allocate monetary assets between entities as part of the provision of financial services.
U. I. Behunkou, M. Y. Kovalyov
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ReLogit: Rare Events Logistic Regression
Journal of Statistical Software, 2003 We study rare events data, binary dependent variables with dozens to thousands of times fewer ones (events, such as wars, vetoes, cases of political activism, or epidemiological infections) than zeros ("nonevents").
Michael Tomz, Gary King, Langche Zeng
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Conditional logistic regression [PDF]
American Journal of Orthodontics and Dentofacial Orthopedics, 2017 In this article, we will describe how to analyze binary data from matched studies in orthodontics. We have previously discussed matched analysis for paired binary data (McNemar test), but now we will focus on the use of regression methods to model our data.1 The idea is the same as with simple logistic regression models for binary data2,3; however, we ...
Nikolaos Pandis, Despina Koletsi
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