Understanding statistical association and correlation

In medical research, the word ‘association’ and ‘correlation’ between two attributes/variables are frequently used and many times interchanged. Simplifying these concepts may help the researchers in applying the appropriate test. The article makes an attempt to simplify the concept of statistical as...

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Bibliographic Details
Main Authors: Ramesh Lal Sapra, Satish Saluja
Format: Article
Language:English
Published: Wolters Kluwer Medknow Publications 2021-01-01
Series:Current Medicine Research and Practice
Subjects:
Online Access:http://www.cmrpjournal.org/article.asp?issn=2352-0817;year=2021;volume=11;issue=1;spage=31;epage=38;aulast=Sapra
Description
Summary:In medical research, the word ‘association’ and ‘correlation’ between two attributes/variables are frequently used and many times interchanged. Simplifying these concepts may help the researchers in applying the appropriate test. The article makes an attempt to simplify the concept of statistical association and correlation, especially for the clinical practitioners and researchers. The article discusses various measures of association and relationship for testing and assessing the strength. It also includes discussion on three popular measures of association used in medical research, namely odds ratio (OR), relative risk (RR) and hazard ratio which measure association of outcome between the two groups. Pearson Chi-square test is the most common test and has been extensively used for studying the association without bothering about its limitations or strength. Many times, researchers take it granted that the OR and RR are one and the same thing. Our calculations suggest us that with probabilities of outcome of 0.5 and 0.1, the OR is 9, whereas RR is 5. Tools for studying the statistical association and correlation should be used cautiously and appropriate tests to be used, particularly when assumptions are violated. While studying the association, its strength should be assessed using the appropriate statistics. OR and RR measure the association for assessing the risk. However, we should avoid equating OR with RR, particularly when the probabilities of outcome are not small.
ISSN:2352-0817
2352-0825