The number of subjects per variable required in linear regression analyses.

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Abstract

To determine the number of independent variables that can be included in a linear regression model.

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Journal

Journal ID (iso-abbrev): J Clin Epidemiol

Title: Journal of clinical epidemiology

ISSN (Electronic): 1878-5921

ISSN (Print): 0895-4356

Publication date (Electronic): Jun 2015

Volume: 68

Issue: 6

Affiliations

[1 ] Institute for Clinical Evaluative Sciences, G1 06, 2075 Bayview Avenue, Toronto, Ontario, Canada M4N 3M5; Institute of Health Policy, Management and Evaluation, University of Toronto, 155 College Street, Suite 425 Toronto, ON M5T 3M6, Canada; Schulich Heart Research Program, Sunnybrook Research Institute, 2075 Bayview Avenue, Toronto, ON M4N 3M5, Canada. Electronic address: peter.austin@ices.on.ca.

[2 ] Department of Public Health, Erasmus MC-University Medical Center Rotterdam, 's-Gravendijkwal 230 3015 CE, Rotterdam, The Netherlands.

Article

Publisher Item ID: S0895-4356(15)00014-1

DOI: 10.1016/j.jclinepi.2014.12.014

PubMed ID: 25704724

SO-VID: ccc28de0-8095-4d82-9a48-47c2eed24e25

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Keywords: Bias,Explained variation,Linear regression,Monte Carlo simulations,Regression,Statistical methods

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Keywords: Bias, Explained variation, Linear regression, Monte Carlo simulations, Regression, Statistical methods

The number of subjects per variable required in linear regression analyses.

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