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Binary logistic regression analysis
Psychiatry and Behavioral Sciences, 2015 In statistics, binary logistic regression analysis is a regression model where the dependent variable is a dichotomous categorical variable. The binary logistic model is used to estimate the probability of a binary response based on one or more ...
Selim Kılıc
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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 +2 more
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Logistic regression analysis of textual data on suicidal ideation [PDF]
PLOS Mental HealthTakafumi Kubota, Takahiro Arai
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Categorical Data Analysis - Logistic Regression
Southwest Respiratory and Critical Care Chronicles, 2014 Shengping Yang, Gilbert Berdine
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Lactation milk yield prediction with possibilistic logistic regression analysis [PDF]
Kafkas Universitesi Veteriner Fakültesi Dergisi, 2021 The logistic regression is a popular method to model the probability of a categorical outcome given as a dependent variable. However, the possibilistic logistic regression can be preferred instead of classical logistic regression when the dependent ...
Derviş TOPUZ
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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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Binary Response Analysis Using Logistic Regression in Dentistry
International Journal of Dentistry, 2022 Multivariate analysis with binary response is extensively utilized in dental research due to variations in dichotomous outcomes. One of the analyses for binary response variable is binary logistic regression, which explores the associated factors and ...
Natchalee Srimaneekarn +3 more
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High performance logistic regression for privacy-preserving genome analysis
BMC Medical Genomics, 2021 Background In biomedical applications, valuable data is often split between owners who cannot openly share the data because of privacy regulations and concerns.
Martine De Cock +5 more
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ANOVA bootstrapped principal components analysis for logistic regression
Croatian Review of Economic, Business and Social Statistics, 2022 Principal components analysis (PCA) is often used as a dimensionality reduction technique. A small number of principal components is selected to be used in a classification or a regression model to boost accuracy.
Toleva Borislava
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Linear and logistic regression analysis [PDF]
Kidney International, 2008 In previous articles of this series, we focused on relative risks and odds ratios as measures of effect to assess the relationship between exposure to risk factors and clinical outcomes and on control for confounding. In randomized clinical trials, the random allocation of patients is hoped to produce groups similar with respect to risk factors.
Tripepi G +3 more
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