Applied Logistic Regression: Hosmer/Applied Logistic Regression

By David W. Hosmer Jr., S. Lemeshow, Rodney X. Sturdivant. 2005

42,941 citations recorded by the source corpus.

Subfields: Management Science and Operations Research, Statistics and Probability

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Citations in the corpus

Stealing Hyperparameters in Machine Learning (2018, methodology): “Popular ML algorithms include ridge regression [19], logistic regression [20], SVM [13], and neural network [16].”
Graph Embedding Techniques, Applications, and Performance: A Survey (2017, methodology): “d and random walk based. Feature-based models [11], [12], [56] generate features for nodes based on their neighborhood and local network statistics and then apply a classiﬁer like Logistic Regression [57] and Naive Bayes [58] to predict the labels. Random walk based models [9], [10] propagate the la”
Computational Phenotype Discovery Using Unsupervised Feature Learning over Noisy, Sparse, and Irregular Clinical Data (2013, methodology): “We chose logistic regression [58] as our classification algorithm because as a simple linear classifier it is more likely to illuminate differences in feature quality than a more sophisticated algorithm such as a support vector machine that would automatically extract complex interactions from…”
A Comparison of Logistic Regression, Classification and Regression Tree, and Neural Networks Models in Predicting Violent Re-Offending (2011, methodology): “Equation 1 represents the definition of the general logistic function (Hosmer and Lemeshow 1989).”
The Focused Information Criterion (2003, methodology): “We consider the dataset given in appendix 1 of Hosmer and Lemeshow (1989), which concerns a study of n D 189 women with newborn babies and factors potentiallyassociated with low infant birth weight, there taken to mean less than 2500 g. Covariate information for the mothers was available as weight…”
Multilevel logistic regression for polytomous data and rankings (2003, methodology): “The polytomous logistic regression model, a standard model for first choices in for instance biostatistics (e.g., Hosmer & Lemeshow, 1989), results as the special case where x a i b = 0 in (4).”
A Primer for Social Worker Researchers on How to Conduct a Multinomial Logistic Regression (2009, methodology): “Hosmer and Lemeshow (2000) point out that “more” or “less” likely would only be true when the odds ratio is believed to be similar to the relative risk.”
Metabolic Syndrome in Childhood: Association With Birth Weight, Maternal Obesity, and Gestational Diabetes Mellitus (2005, positive): “Obesity (BMI 85th percentile) Age 6 y 13/39 (33) 7/49 (14) 11/41 (27) 9/41 (22) Age 7 y 14/35 (40) 3/49 (6) 10/41 (24) 10/37 (27) Age 9 y 10/23 (44) 9/34 (26) 7/25 (28) 7/25 (28) Age 11 y 7/20 (35) 9/38 (24) 8/26 (31) 6/25 (24) BP 90th percentile* Age 6 y 7/34 (21) 15/47 (31) 4/40 (10) 8/40 (20) Age”
Creating College Opportunity: School Counselors and Their Influence on Postsecondary Enrollment (2013, methodology): “…linear model I incorporated into my study employed a multinomial logit link function—which is suitable for estimating categorical outcomes (Hosmer and Lemeshow 1989) and for the study of postsecondary enrollment (Cabrera 1994)—to distinguish between the differing influence counseling may…”
A statistical investigation of preearthquake ionospheric anomaly (2006, methodology): “[9] Moreover, on the basis of the 93 earthquake days, the fitted logistic regression models [Hosmer and Lemeshow, 1989] for the logarithm of the odds of the earthquakes with the PEIA against the corresponding magnitude and distance, respectively, are log p= 1 pð Þf g ¼ 6:96þ 1:50M and log p=ð1 pÞf…”
Private supplementary tutoring among primary students in Bangladesh (2008, methodology): “As the dependent variable was dichotomous in nature (having incidence of private tutor or not), binary logistic regression analysis was considered to be suitable (Menard 1995; Hosmer and Leweshow 1989).”
Considering, planning, and realizing migration in early adulthood. The influence of life-course events and perceived opportunities on leaving the city in Germany (2010, background): “In that case weighting is usually not necessary and not recommended because of a loss in efficiency of the parameters (Hosmer and Lemeshow 1989; Winship and Radbill 1994).”