What was found to be greater than the positive predictive value based on provided calculations?

The negative predictive value (NPV) is calculated based on the number of true negatives divided by the total number of negative test results, which can often lead to it being greater than the positive predictive value (PPV). This is particularly true in screening tests or diagnostic scenarios where the prevalence of the condition being tested for is low.

When the prevalence of a disease is low, there will be more true negatives relative to false positives, leading to a higher NPV. In contrast, PPV, which measures the proportion of positive test results that are true positives, can be significantly influenced by the number of false positives, especially when the condition is less common.

This context helps clarify why the negative predictive value could be greater than the positive predictive value under certain circumstances, making it the correct choice in this scenario.