Concurrent validity is a measure of how well a particular test correlates with a previously validated measure. It is commonly used in social science, psychology and education.
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The tests are for the same, or very closely related, constructs and allow a researcher to validate new methods against a tried and tested stalwart.
For example, IQ, Emotional Quotient, and most school grading systems are good examples of established tests that are regarded as having a high validity. One common way of looking at concurrent validity is as measuring a new test or procedure against a gold-standard benchmark.
Concurrent Validity - A Question of Timing
As the name suggests, concurrent validity relies upon tests that took place at the same time. Ideally, this means testing the subjects at exactly the same moment, but some approximation is acceptable.
For example, testing a group of students for intelligence, with an IQ test, and then performing the new intelligence test a couple of days later would be perfectly acceptable.
If the test takes place a considerable amount of time after the initial test, then it is regarded as predictive validity. Both concurrent and predictive validity are subdivisions of criterion validity and the timescale is the only real difference.
An Example of Concurrent Validity
Researchers give a group of students a new test, designed to measure mathematical aptitude.
They then compare this with the test scores already held by the school, a recognized and reliable judge of mathematical ability.
Cross referencing the scores for each student allows the researchers to check if there is a correlation, evaluate the accuracy of their test, and decide whether it measures what it is supposed to. The key element is that the two methods were compared at about the same time.
If the researchers had measured the mathematical aptitude, implemented a new educational program, and then retested the students after six months, this would be predictive validity.
The Weaknesses of Concurrent Validity
Concurrent validity is regarded as a fairly weak type of validity and is rarely accepted on its own. The problem is that the benchmark test may have some inaccuracies and, if the new test shows a correlation, it merely shows that the new test contains the same problems.
For example, IQ tests are often criticized, because they are often used beyond the scope of the original intention and are not the strongest indicator of all round intelligence. Any new intelligence test that showed strong concurrent validity with IQ tests would, presumably, contain the same inherent weaknesses.
Despite this weakness, concurrent validity is a stalwart of education and employment testing, where it can be a good guide for new testing procedures. Ideally, researchers initially test concurrent validity and then follow up with a predictive validity based experiment, to give a strong foundation to their findings.
Craighead, W.E., & Nemeroff, C.B. (2004). The Concise Corsini Encyclopedia of Psychology and Behavioral Sciences (3rd Ed.).
Stevens, J.P. (2009). Applied Multivariate Statistics for the Social Sciences. Fifth Edition. New York: Routledge. Hoboken, NJ: John Wiley