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**Criterion validity** refers to how well the measurement of one variable can predict the response of another variable.

One variable is referred to as the explanatory variable while the other variable is referred to as the criterion variable.

For example, we might want to know how well some college entrance exam is able to predict the first semester grade point average of students.

The entrance exam would be the explanatory variable and the criterion variable would be the first semester GPA.

We want to know if it’s *valid* to use this particular explanatory variable as a way to predict the criterion variable.

**How to Measure Criterion Validity**

We typically measure criterion validity using a metric like the Pearson Correlation Coefficient, which takes on value between -1 and 1 where:

- -1 indicates a perfectly negative linear correlation between two variables
- 0 indicates no linear correlation between two variables
- 1 indicates a perfectly positive linear correlation between two variables

The further away the correlation coefficient is from zero, the stronger the association between the two variables.

For example, if we collected data on entrance exam scores and first semester GPA for 1,000 students and found that the correlation between the two variables was **0.843** then this would mean the two variables are highly correlated.

In other words, students who score high on the entrance exam also tend to earn high GPA’s during their first semester. Conversely, students who score low on the entrance exam tend to earn low GPA’s during their first semester.

**Types of Criterion Validity**

There are two main types of criterion validity:

The first type of criterion validity is known as predictive validity, which determines whether or not the measurement of one variable is able to accurately predict the measurement of some variable in the future.

The previous example of measuring a student’s college entrance exam score and their first semester GPA is an example of measuring predictive validity because we measure the two variables at different points in time.

In other words, we’re trying to determine if the entrance exam score can *predict* first semester GPA well.

The second type of criterion validity is known as concurrent validity, which measures two variables *concurrently* (i.e. at the same time) to see if one variable is significantly associated with the other.

An example of this would be if a company administers some type of test to see if the scores on the test are correlated with employee productivity.

The benefit of this approach is that we don’t have to wait until some point in the future to take a measurement on the criterion variable we’re interested in.