Applied Logistic Regression

By Joseph D. Conklin. Technometrics, 2002

5,422 citations recorded by the source corpus.

Subfields: Management Science and Operations Research, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/ff1530f35ba2e6e067ef421562d8cfe324ec8843

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In Management Science and Operations Research

In Statistics and Probability

Citations in the corpus

The TIMI risk score for unstable angina/non-ST elevation MI: A method for prognostication and therapeutic decision making. (2000, neutral): “The goodness of fit of the model to the observed event rates was evaluated by calculating the Hosmer-Lemeshow statistic.(27) Low x(2) values and high corresponding P values for the Hosmer-Lemeshow statistic indicate that the data can be adTHE TIMI RISK SCORE FOR UNSTABLE ANGINA”
Relation of impaired fasting and postload glucose with incident type 2 diabetes in a Dutch population: The Hoorn Study. (2001, methodology): “The Hosmer-Lemeshow goodness-offit test was used to assess the overall fit of the logistic regression model.(20) The OR is the ratio of the odds of 2 categories and can be interpreted as an approximation of the relative risk.”
The relative importance of dispersal limitation of vascular plants in secondary forest succession in Muizen Forest, Belgium (2001, neutral): “The resulting ‘odds ratios’ that indicate how much more likely it is that a species is present when the secondary forest age is increased by one class (Hosmer & Lemeshow 1989), allowed us to rank the species according to their affinity with older forest.”
Predicting In-Hospital Mortality of ICU Patients: The PhysioNet/Computing in Cardiology Challenge 2012 (2012, methodology): “The scoring for event 2 was based on a modiﬁed version of the Hosmer-Lemeshow statistic [9], H .”
Analyzing and Predicting Students’ Performance by Means of Machine Learning: A Review (2020, methodology): “…several algorithms and comparing their results will be always very useful, as in [6], where four classiﬁcation algorithms (Logistic Regression (LR) [67], DT, ANN, and SVM) were compared with three data balancing techniques: Over-Sampling, Under-Sampling, and Synthetic Minority Over-Sampling…”
Self-concordant analysis for logistic regression (2009, neutral): “, [9, 10]), leading to iterative least-squares algorithms, we don’t focus in the paper on the resolution of the optimization problems, but on the statistical analysis of the associated global minimizers.”
Logistic regression in the medical literature: standards for use and reporting, with particular attention to one medical domain. (2001, methodology): “Selection of predictor variables Does the article explain how variables were selected for inclusion into the model? Usually the variables are chosen based on earlier research; sometimes they are selected by virtue of significant association in a bivariate analysis with the outcome variable [4].”
Exposure to dogs and cats in the first year of life and risk of allergic sensitization at 6 to 7 years of age. (2002, methodology): “Atopy and seroatopy were each used as a dependent binary variable in a linear logistic regression assessing 2 indicator variables for pet exposure: exposure to 1 dog or cat or exposure to 2 or more dogs or cats.(35) These models were fitted without other variables and with other potentially confound”
Rethinking financial contagion: Information transmission mechanism during the COVID-19 pandemic (2020, neutral): “They adopted multinomial logistic analysis that has been extensively used in epidemiology research on contagion diseases, for example by Hosmer and Lemeshow (1989), to analyse the transmission of information across regions and within regions.”
Dynamic wildlife habitat models: Seasonal foods and mortality risk predict occupancy-abundance and habitat selection in grizzly bears (2010, methodology): “In the case of the Hosmer and Lemeshow (2000) model selection approach, the highest-ranked uncorrelated factors were introduced individually in a forward manner until all significant (p 0.1) factors were retained.”