Concurrent validity is demonstrated where a test correlates well with a measure that has previously been validated. The two measures may be for the same construct, or for different, but presumably related, constructs. In statistics a valid measure is one which is measuring what it is supposed to measure. ...
For example, if a test measuring job satisfaction gives similar results to those gathered using a job satisfaction which has been validated in past investigations the new measurement has concurrent validity. Alternately, a measure of job satisfaction might be correlated with work performance. Note that with concurrent validity, the two measures are taken at the same time. This is in contrast to predictive validity, where one measure occurs earlier, and is meant to predict, some later criterion measure.
A common approach, called criterion validity, is to correlate measures with a criterion measure known to be valid.
When the criterion measure is collected at the same time as the measure being validated the goal is to establish concurrentvalidity; when the criterion is collected later the goal is to establish predictive validity.
According to classical test theory, predictive or concurrentvalidity cannot exceed the square of the correlation between two versions of the same measure -- that is, validity cannot exceed reliability.
For example, the validity of a cognitive test for job performance is the correlation between test scores and, say, supervisor performance ratings.
Predictive validity shares similarities with concurrentvalidity in that both are generally measured as correlations between a test and some criterion measure.
In a study of concurrentvalidity the test is administered at the same time as the criterion is collected.
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