BASIC STATISTICS FOR CLINICIAN .4. CORRELATION AND REGRESSION

Citation
G. Guyatt et al., BASIC STATISTICS FOR CLINICIAN .4. CORRELATION AND REGRESSION, CMAJ. Canadian Medical Association journal, 152(4), 1995, pp. 497-504
Citations number
9
Categorie Soggetti
Medicine, General & Internal
ISSN journal
08203946
Volume
152
Issue
4
Year of publication
1995
Pages
497 - 504
Database
ISI
SICI code
0820-3946(1995)152:4<497:BSFC.C>2.0.ZU;2-C
Abstract
Correlation and regression help us to understand the relation between variables and the predict patients' status in regard to a particular v ariable of interest. Correlation examines the strength of the relation between two variables, neither of which is considered the variable on e is trying to predict (the target variable). Regression analysis exam ines the ability of one or more factors, called independent variables, to predict a patients status in regard to the target or dependent var iable. Independent and dependent variables may be continuous (taking a wide range of values) or binary (dichotomous, yielding yes-on-no resu lts). Regression models can be used to construct clinical prediction r ules that help to guide clinical decisions. In considering regression and correlation, clinicians should pay more attention to the magnitude of the correlation or the predictive power of the regression than to whether the relation is statistically significant.