Cited by 496Statistical Methods in EpidemiologyStatistical Methods and Bayesian InferenceStatistical Methods and Applications

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The importance of assessing the fit of logistic regression models: a case study.

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Hosmer, D W, Taber, S, Lemeshow, S·1991·American Journal of Public Health

DOI 10.2105/ajph.81.12.1630PMC PMC1405276

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Abstract

BACKGROUND: The logistic regression model is being used with increasing frequency in all areas of public health research. In the calendar year 1989, over 30% of the articles published in the American Journal of Public Health employed some form of logistic regression modeling. In spite of this increase, there has been no commensurate increase in the use of commonly available methods for assessing model adequacy. METHODS: We review the current status of the use of logistic regression modeling in the American Journal of Public Health. We present a brief overview of currently available and easily used methods for assessing the adequacy of a fitted logistic regression model. RESULTS: An example is used to demonstrate the methods as well as a few of the adverse consequences of failing to assess the fit of the model. One important adverse consequence illustrated in the example is the inclusion of variables in the model as a result of the influence of one subject. CONCLUSIONS: Failure to address model adequacy may lead to misleading or incorrect inferences. Recommendations are made for the use of methods for assessing model adequacy and for future editorial policy in regard to the review of articles using logistic regression.

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Authors: Hosmer, D. W., Taber, S., & Lemeshow, S.
Affiliations: University of Massachusetts Amherst (US)
Venue: American Journal of Public Health
Publisher: American Public Health Association
Published: 1991-12
Volume: 81
Issue: 12
Pages: 1630-1635
ISSN: 0090-0036 (ISSN-L)
1541-0048
DOI: 10.2105/ajph.81.12.1630
PMC: PMC1405276
OpenAlex: W1984363050
Cited by: 496
References: 7
Citations by year: 2026: 11 · 2025: 7 · 2024: 18 · 2023: 9 · 2022: 16 · 2021: 19 · 2020: 15 · 2019: 17 · 2018: 8 · 2017: 14 · 2016: 13 · 2015: 21 · 2014: 14 · 2013: 28 · 2012: 27
FWCI: 6.55
Type: journal article
Language: en
Open access: bronze
doi.org
Locations: American Journal of Public Health (publishedVersion)
PubMed Central (publishedVersion)
PubMed (publishedVersion)
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, model fit assessment, model adequacy, influential observations, editorial policy, statistical reporting quality, public health research
MeSH terms: Data Interpretation, Statistical, Evaluation Studies as Topic, Humans, Periodicals as Topic, Public Health, Publishing, Reproducibility of Results, Bias, Logistic Models

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The importance of assessing the fit of logistic regression models: a case study.

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