The DOI matches its Crossref record; 7 of the 7 references it cites were found in a registry or an index.
The Risk of Determining Risk with Multivariable Models
Abstract
PURPOSE: To review the principles of multivariable analysis and to examine the application of multivariable statistical methods in general medical literature. DATA SOURCES: A computer-assisted search of articles in The Lancet and The New England Journal of Medicine identified 451 publications containing multivariable methods from 1985 through 1989. A random sample of 60 articles that used the two most common methods--logistic regression or proportional hazards analysis--was selected for more intensive review. DATA EXTRACTION: During review of the 60 randomly selected articles, the focus was on generally accepted methodologic guidelines that can prevent problems affecting the accuracy and interpretation of multivariable analytic results. RESULTS: From 1985 to 1989, the relative frequency of multivariable statistical methods increased annually from about 10% to 18% among all articles in the two journals. In 44 (73%) of 60 articles using logistic or proportional hazards regression, risk estimates were quantified for individual variables ("risk factors"). Violations and omissions of methodologic guidelines in these 44 articles included overfitting of data; no test of conformity of variables to a linear gradient; no mention of pertinent checks for proportional hazards; no report of testing for interactions between independent variables; and unspecified coding or selection of independent variables. These problems would make the reported results potentially inaccurate, misleading, or difficult to interpret. CONCLUSIONS: The findings suggest a need for improvement in the reporting and perhaps conducting of multivariable analyses in medical research.
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A leisurely look at the bootstrap, the jackknife, and cross-validation
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Physical Fitness as a Predictor of Cardiovascular Mortality in Asymptomatic North American Men
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A simulation study of the number of events per variable in logistic regression analysis
Peduzzi, P., Concato, J., Kemper, E., Holford, T. R., & Feinstein, A. R. (1996) · Journal of Clinical Epidemiology · doi:10.1016/s0895-4356(96)00236-3 · Cited by 9,655
Self-citationMoher, D., Hopewell, S., Schulz, K. F., Montori, V., Gotzsche, P. C., Devereaux, P. J., Elbourne, D., Egger, M., & Altman, D. G. (2010) · BMJ · doi:10.1136/bmj.c869 · Cited by 8,883
Moons, K. G. M., Altman, D. G., Reitsma, J. B., Ioannidis, J. P. A., Macaskill, P., Steyerberg, E. W., Vickers, A. J., Ransohoff, D. F., & Collins, G. S. (2015) · Annals of Internal Medicine · doi:10.7326/m14-0698 · Cited by 5,147
The Revised CONSORT Statement for Reporting Randomized Trials: Explanation and Elaboration
Altman, D. G., Schulz, K. F., Moher, D., Egger, M., Davidoff, F., Elbourne, D., Gøtzsche, P. C., Lang, T., & for the CONSORT Group (2001) · Annals of Internal Medicine · doi:10.7326/0003-4819-134-8-200104170-00012 · Cited by 3,835
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Metadata
- Authors
- Concato, J., Feinstein, A. R., & Holford, T. R.
- Venue
- Annals of Internal Medicine
- Publisher
- American College of Physicians
- Published
- 1993-02-01
- Volume
- 118
- Issue
- 3
- Pages
- 201-210
- ISSN
- 0003-4819 (ISSN-L)
- 1539-3704
- OpenAlex
- W2094104004
- Cited by
- 1,115
- References
- 7
- FWCI
- 41.21
- Type
- journal article
- Language
- en
- Open access
- closed
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