Predictive validity measures how well a test predicts future performance by comparing it to known criteria. College entrance tests are an example, but there are weaknesses, including missing data and potential bias. Statistical significance is difficult to calculate, but it is commonly used in psychological studies and by companies to evaluate prospective employees.
Predictive validity is a measure of how well a test predicts future performance. It is a form of criterion validity, in which the performance of the test is established by measuring it against known criteria. For a test to have predictive validity, there must be a statistically significant correlation between test scores and the criterion used to measure validity.
One of the classic examples of this is the college entrance test. When students apply to colleges, they are usually required to submit test scores from exams such as the SAT or ACT. These scores are used as a basis for comparison, with raters looking at the performance of students who have had similar tests in the past. The belief is that test scores can predict how well a student will perform in college. High test scores tend to correlate with good college performance, making high scoring students attractive to admissions departments.
The example of college test scores is also an excellent example of the weaknesses of predictive validity. Some students who take such tests don’t go to college, which means no data is generated to correlate test scores and college performance. This creates a hole in the data set, which can undermine the validity of such tests. Standardized tests have also been accused of some bias that can work against particular students, especially students from racial minorities. They may do poorly on the test and do well in college, skewing the results.
Statistical significance can be difficult to calculate. A huge number of factors can affect test results, especially when they involve data from a test and a criterion measure that is collected at different points. Predictive validity affects everything from health insurance rates to college admissions, with people using statistical data to try to predict people’s futures based on the information that can be gleaned about them from tests.
Predictive validity is most commonly used when exploring data in the field of psychological study and analysis. It is used to gather information about various populations and to make generalizations that can be useful when evaluating individuals. For example, it is often used by large companies that administer a test to prospective employees, comparing test data from current employees to determine whether or not someone will be a good fit for the company.
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