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
Categorie Soggetti
Medicine, General & Internal
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.