TY - JOUR
T1 - The use of correlation and regression methods in optometry
AU - Armstrong, Richard A.
AU - Eperjesi, Frank
AU - Gilmartin, Bernard
PY - 2005/3
Y1 - 2005/3
N2 - Correlation and regression are two of the statistical procedures most widely used by optometrists. However, these tests are often misused or interpreted incorrectly, leading to erroneous conclusions from clinical experiments. This review examines the major statistical tests concerned with correlation and regression that are most likely to arise in clinical investigations in optometry. First, the use, interpretation and limitations of Pearson's product moment correlation coefficient are described. Second, the least squares method of fitting a linear regression to data and for testing how well a regression line fits the data are described. Third, the problems of using linear regression methods in observational studies, if there are errors associated in measuring the independent variable and for predicting a new value of Y for a given X, are discussed. Finally, methods for testing whether a non-linear relationship provides a better fit to the data and for comparing two or more regression lines are considered.
AB - Correlation and regression are two of the statistical procedures most widely used by optometrists. However, these tests are often misused or interpreted incorrectly, leading to erroneous conclusions from clinical experiments. This review examines the major statistical tests concerned with correlation and regression that are most likely to arise in clinical investigations in optometry. First, the use, interpretation and limitations of Pearson's product moment correlation coefficient are described. Second, the least squares method of fitting a linear regression to data and for testing how well a regression line fits the data are described. Third, the problems of using linear regression methods in observational studies, if there are errors associated in measuring the independent variable and for predicting a new value of Y for a given X, are discussed. Finally, methods for testing whether a non-linear relationship provides a better fit to the data and for comparing two or more regression lines are considered.
KW - comparison of regression lines
KW - correlation
KW - goodness of fit
KW - non-linear regression
KW - prediction
UR - http://www.scopus.com/inward/record.url?scp=18344393811&partnerID=8YFLogxK
UR - http://onlinelibrary.wiley.com/doi/10.1111/j.1444-0938.2005.tb06672.x/abstract
U2 - 10.1111/j.1444-0938.2005.tb06672.x
DO - 10.1111/j.1444-0938.2005.tb06672.x
M3 - Article
C2 - 15807639
SN - 0816-4622
VL - 88
SP - 81
EP - 88
JO - Clinical and Experimental Optometry
JF - Clinical and Experimental Optometry
IS - 2
ER -