The use of correlation and regression methods in optometry

Richard A. Armstrong, Frank Eperjesi, Bernard Gilmartin

Research output: Contribution to journalArticlepeer-review


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.

Original languageEnglish
Pages (from-to)81-88
Number of pages8
JournalClinical and Experimental Optometry
Issue number2
Publication statusPublished - Mar 2005


  • comparison of regression lines
  • correlation
  • goodness of fit
  • non-linear regression
  • prediction


Dive into the research topics of 'The use of correlation and regression methods in optometry'. Together they form a unique fingerprint.

Cite this