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Applied logistic regression
Abstract
A new edition of the definitive guide to logistic regression modeling for health science and other applications This thoroughly expanded Third Edition provides an easily accessible introduction to the logistic regression (LR) model and highlights the power of this model by examining the relationship between a dichotomous outcome and a set of covariables. Applied Logistic Regression, Third Edition emphasizes applications in the health sciences and handpicks topics that best suit the use of modern statistical software. The book provides readers with state-of-
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“This sample size was chosen taking into account approximate sample size estimation criteria [38,39]. We worked with the criteria that 10 subjects would be needed per parameter included in a statistical model used to adjust for confounding.”
From Relationships, love and sexuality: what the Filipino teens think and feel (2009) · cites this paper as [39]
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Metadata
- Authors
- Hosmer, D. W., Lemeshow, S. A., & Sturdivant, R. X.
- Venue
- Choice Reviews Online
- Publisher
- American Library Association
- Published
- 1990-02-01
- Volume
- 27
- Issue
- 06
- Pages
- 27-3338-27-3338
- ISSN
- 0009-4978 (ISSN-L)
- 1523-8253
- OpenAlex
- W1973948212
- Cited by
- 35,305
- References
- 0
- Citations by year
- 2026: 8 · 2025: 9 · 2024: 36 · 2023: 33 · 2022: 67 · 2021: 1072 · 2020: 1196 · 2019: 1195 · 2018: 1126 · 2017: 1233 · 2016: 1441 · 2015: 1657 · 2014: 1894 · 2013: 1846 · 2012: 1861
- Type
- book review
- Language
- en
- Open access
- closed
- Locations
- Choice Reviews Online (publishedVersion)
- International Linear Collider (submittedVersion)
- CERN Document Server (European Organization for Nuclear Research) (submittedVersion)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Bayesian Inference
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Applications
- Keywords
- logistic regression, binary outcomes, covariates, health sciences, statistical software, binary response models
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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