What is Criterion Validity?

Criterion validity refers to a test’s correlation with a concrete outcome. It’s also known as concrete validity, and it’s the most powerful way to establish a pre-employment test’s validity.  

What are the types of criterion validity?

There are two main types of criterion validity: concurrent validity and predictive validity. 

Concurrent validity is determined by comparing tests scores of current employees to a measure of their job performance. Comparing test scores with current performance ratings demonstrates how correlated the test is for current employees in a particular position. 

For example, a company could administer a sales personality test to its sales staff to see if there is an overall correlation between their test scores and a measure of their productivity.

Predictive validity, however, is determined by seeing how likely it is that test scores predict future job performance. If an employer's selection testing program is truly job-related, it follows that the results of its selection tests should accurately predict job performance. In other words, there should be a positive correlation between test scores and future job performance. 

Determining predictive validity is a long-term process that involves testing job candidates and then comparing their test scores to a measure of their job performance after they have occupied their positions for a long period of time.

Why is criterion validity important for pre-employment testing? 

In the case of pre-employment tests, criterion validity is what establishes the connection between a test score and a business metric. The more correlated test scores are with job performance, the more likely the test is to predict future job performance. And as with most correlations, criterion validity can only be established with large sample sizes, making it somewhat challenging to measure.

For example, the two variables being compared most frequently are test scores and a particular business metric, such as employee performance or retention rates.

The relationship between test performance and a business metric can be quantified by a correlation coefficient (ranging from -1.0 to +1.0), which is used to demonstrate how strongly correlated two variables are, depending on how close the number is to -1.0 or +1.0. The more correlated the two variables are, the more predictive validity the test has.