Analysis With Sensitivity and Specificity Ranges

¶ … conducive to generating authentic results; Test a that has a 95/75% sensitivity/specificity rating or Test B that has a 75/95% rating. Choosing Test B is the sensible choice regarding this particular study. First of all, the researcher intends on using participants who have already tested positive for Q. Since it can be assumed that all the participants are suffering from Q then the predictor would show a 75% rate of all the sufferers will be identified as suffers.

At the same time, Test B has a specificity rate of 95% which means that 95% of the participants who are tested as negative will actually be negative. Abobaker (2015) used the same type of test to determine a diagnosis of sonographically detected abdominal masses in a similar scenario and was able to conclude a high level of sensitivity and specificity.

Since the researcher is attempting to determine how many participants are affected once a variable has been introduced into the study, it would seem likely that the researcher was also looking to be able to track the number of false positives (the number of participants who are testing positive when they are not positive) while at the same time tracking the number of false negatives (the number of participants who present as not having suffering from condition Q.

In Test A, the sensitivity rate of 95% can best describe the situation as showing that only 5% of the participants are not testing as positive even though the researcher knows that every participant has already been shown to be suffering from the condition. On the other hand using Test B would show that 25% of the participants were not actually suffering from condition Q; those results could be more easily justified precisely because the researcher already knew that every participant had already presented with the condition.

Another study (Simas, Chattopadhyay, Hagan, Kundu, Patel, Holt, Floris, Graham, Ooi, Tait, Spencer, Baron-Cohen, Sahakian, Bullmore, Goodyer, Suckling, 2015) was able to conclude that the sensitivity and specificity of their study provided a best case finding in a two-case control analysis of independent, matched groups of participants all suffering from the same condition (autism spectrum conditions) as well as major depressive disorder (MDD). The Simas (2015) study was able to determine that the methodology was potentially capable of detecting and characterizing "a range of disorders" (p. 2).

This proposed study is certainly not looking to detect a wide range of disorders, but the similarities in the manner in which the study was carried out, provides justification for using Test B.

Of course, in a world where higher authenticity rates are coveted, a perfect score on both specificity and sensitivity would be 100%; since neither one of these two tests have earned the distinction of being perfect, it makes more sense to use the test that is more likely to have a lower percentage of false negatives than the test that would determine a lower number of false positives.

There is a case to be made for both tests, Test A can show that there is a relatively lower amount of false positives which is a good thing.