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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, C S Pramesh, Rakesh Aggarwal   +2 more
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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, Anthony Hayter, Wei Liu, Chanita Tantipoj   +3 more
doaj   +2 more sources

Logistic Regression Analysis for Spatial Patterns of Drought Persistence

Complexity, 2021
Drought is one of the natural hazards with potentially significant impacts on society, economy, and other natural resources over the globe. However, the understanding of drought characteristics and its persistence can significantly help to reduce the ...
Rizwan Niaz, Xiang Zhang, Nouman Iqbal, Mohammed M.A. Almazah, Tajammal Hussain, Ijaz Hussain   +5 more
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Understanding logistic regression analysis [PDF]

Biochemia Medica, 2014
La régression logistique est utilisée pour obtenir le rapport de cotes en présence de plus d'une variable explicative. La procédure est assez similaire à la régression linéaire multiple, à l'exception que la variable de réponse est binomiale. Le résultat est l'impact de chaque variable sur le rapport de cotes de l'événement d'intérêt observé.
Sandro Sperandei
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Logistic regression analysis of textual data on suicidal ideation. [PDF]

PLOS Mental Health
Suicide prevention requires careful consideration of the entire process, including ideation, attempt, and death. Understanding factors related to suicidal ideation is particularly critical for early intervention and effective prevention measures. In this
Takafumi Kubota, Takahiro Arai
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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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Applying the Binary Logistic Regression Analysis on The Medical Data

Science Journal of University of Zakho, 2017
In this paper, the Binary Logistic Regression Analysis BLRA technique has been used and applied for building the best model for Hepatitis disease data using best subsets regression and stepwise procedures and depending on some laboratory tests such as ...
Qais M. Abdulqader
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Logistic regression analysis on the determinants of stillbirth in Ethiopia [PDF]

Maternal Health, Neonatology and Perinatology, 2016
غالبًا ما يتم تعريف الإملاص على أنه وفاة الجنين بعد 24 أسبوعًا من الحمل، ولكن يمكن اعتبار الجنين أكبر من أي مزيج من 16 أو 20 أو 22 أو 24 أو 28 أسبوعًا من عمر الحمل و 350 جم أو 400 جم أو 500 جم أو 1000 جم من وزن الولادة ميتًا اعتمادًا على القانون المحلي. بمجرد وفاة الجنين، قد تتعرض الأم أو لا تتعرض لانقباضات وتخضع للولادة أو في بعض الحالات، عملية قيصرية.
Kidanemariam Alem Berhie, Habtamu Gebremariam Gebresilassie   +1 more
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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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