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Concurrent validity A stronger way of testing validity of an indicator is to establish a strong relationship between the indicator and some external criterion. This approach is known as establishing concurrent validity. It is also referred to as criterion validity because it depends on use of an external criterion. The criterion is selected because the persons or other units of analysis are known to differ greatly in terms of the concept being measured. For example, Kridli (1997) wished to establish the validity of a set of questions for measuring the intention of Jordanian Muslim women to use oral contraceptives. One of the validity tests she used was to compare differences in responses for women who were known to have used oral contraceptives with those who had not. Kridli reasoned that past users would answer more positively than non-users. And this is what she found. Kridli properly accepted these results as evidence for the validity of the indicator for intended use of oral contraceptives. Predictive validity In testing for predictive validity, the investigator uses a future criterion measure in place of a concurrent one. Suppose we wanted to develop a written test for estimating the success in college of secondary students based on their performance as secondary students. First, we would have to decide on indicators of the students' performance at the secondary level. Let's say we decide to use a combination of the students' knowledge of secondary school subjects and their ability to think clearly and logically as indicators of their likely success in college. We have the students take a test that includes measures of both indicators. To test the validity of our measuring instrument for predicting success in college, we decide to use the students' accumulated grade point average at the end of their first year in college. These averages become the criterion for testing the validity of the "college success" measure based on secondary school performance. A statistical test would then be used to measure the relationship between the results of the tests given at the secondary school level and the accumulated grade point averages of the students at the end of their first year of college. A high relationship between the two sets of scores would provide evidence that the measure of secondary school performance is a valid predictor of success in college, as measured by one criterion - the students' accumulated grade point averages. Interpreting validity tests When the expected results are obtained, an indicator can be considered as a valid measure. But how should the data be interpreted when the expected results are not found? What if Kridli (1997) had found that the past users and non-users of oral contraceptives had given about the same responses to the test she was developing? What if the accumulated grade point averages of college students were about the same for those who had low as opposed to those who had high accumulated grade point averages a the end of their first year in college? When validity fails to produce the expected results, investigators have to sort out the reason why. Negative results can occur for four reasons. These include:
When negative results occur, the researcher has to seek new criteria for validating the indicator, seek improved measurement of indicator and the criterion, or do all these things. There is a lot more to establishing claims for the validity of a measure. If you want to dig deeper, take a look at Measurement Validity Type. This site provides an alternative way of thinking about validity. Validity is presented in terms of how well a concept is translated into an operational measure. If you speak another language, you know there are good, bad, and very bad translations: so too with establishing claims for validity. In effect, how well did the researcher achieve a translation of a concept or construct into an operational measure? |