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The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

Importance of events per independent variable in proportional hazards analysis I. Background, goals, and general strategy

Open access
Concato, John, Peduzzi, Peter, Holford, Theodore R., Feinstein, Alvan R.·1995·Journal of Clinical Epidemiology

Abstract

Multivariable methods of analysis can yield problematic results if methodological guidelines and mathematical assumptions are ignored. A problem arising from a too-small ratio of events per variable (EPV) can affect the accuracy and precision of regression coefficients and their tests of statistical significance. The problem occurs when a proportional hazards analysis contains too few "failure" events (e.g., deaths) in relation to the number of included independent variables. In the current research, the impact of EPV was assessed for results of proportional hazards analysis done with Monte Carlo simulations in an empirical data set of 673 subjects enrolled in a multicenter trial of coronary artery bypass surgery. The research is presented in two parts: Part I describes the data set and strategy used for the analyses, including the Monte Carlo simulation studies done to determine and compare the impact of various values of EPV in proportional hazards analytical results. Part II compares the output of regression models obtained from the simulations, and discusses the implication of the findings.

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Metadata

Authors
Concato, J., Peduzzi, P., Holford, T. R., & Feinstein, A. R.
Venue
Journal of Clinical Epidemiology
Publisher
Elsevier BV
Published
1995-12
Volume
48
Issue
12
Pages
1495-1501
ISSN
0895-4356 (ISSN-L)
OpenAlex
W1982245010
Cited by
797
References
1
FWCI
2.17
Type
journal article
Language
en
Open access
hybrid

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