Talk:Specificity (tests)

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In gene structure prediction literature, specificity has traditionally been computed as . That is, S_p is the proportion of predicted coding nucleotide that are actually coding. 22:31, 15 Aug 2004

The problem with using specificity that way is that it does not tell you much about the procedure or test, since it depends on what proportion of the underlying population is in fact positive or negative. --Henrygb 19:36, 22 Nov 2004 (UTC)

It would be nice to see a credible reference if you have one. I think you are talking about positive predictive value. --Henrygb 02:36, 12 Mar 2005 (UTC)

I'm not sure what you mean by credible reference, but Burset and Guigo (1996) defines specificity in this way. That's not to say that it's correct. As they say in a later paper (free full text), "we essentially compute the proportion of actual coding nucleotides/exons that have been predicted correctly-(which we call Sensitivity) and the proportion of predicted coding nucleotides/exons that are actually coding nucleotides/exons (which we call Specificity)". Thus, it may not be correct, but it has become the standard. That said, the gene finding definition of specificity appears to be the same as precision from Information Retrieval, i.e. "(number of relevant documents retrieved) / (number of documents retrieved)". This corresponds to TP/(TP+FP). Thus, there seems to be some conflict in this article, which states that specificity is the same as precision. It is not. 24.63.115.69 06:55, 15 September 2005 (UTC)

Fair enough, I asked for a reference and you kindly provided one. I still think it is an error: the CDC in their pages on Genomics use the standard definition [1]. Meanwhile someone else manages to use "specificity" to produce a number 10^13,167,898. I read the article as saying that positive predictive value and precision are equivalent, and that both depend on the underlying population, which specificity does not. --Henrygb 13:49, 15 September 2005 (UTC)

[edit] continuous interpretation of specificity (for instrumentation)

I came to this page looking for a continuous interpretation of specificity (for instrumentation). For example if you built an instrument to measure the salt content of a solution, it might (by imperfect design) also register the amount of sugar in the sample. Suppose the actual instrument reading was [reading] = 0.99*[true salt concentration] + 0.01*[sugar concentration]. Is there a concept of specificity that characterizes this kind of imperfection? 69.159.205.193 14:07, 15 February 2006 (UTC)

Such a thing does not fall under information retrieval definitions of specificity. What you are actually looking for is a statistical method to give you a confidence interval for the salt concentration... --Jettlogic

[edit] Reference for IR and binary classification measures

This is based on http://www.musc.edu/dc/icrebm/sensitivity.html

Information Retrieval

   Basics
       True Positives (TP)
           "Number of P's that you called P"
       True Negatives (TN)
           "Number of N's that you called N"
       False Positives (FP)
           "Number of N's that you called P" (Type I errors)
       False Negatives (FN)
           "Number of P's that you called N" (Type II errors)
       Positives (P=TP+FN)
           "Number of P's"
       Negatives (N=TN+FP)
           "Number of N's"
       Data set (A=P+N)
           "Number of P's and N's"
   Sensitivity (TP/P)
       "Proportion of P's that you called P" (recall in IR)
   Specificity (TN/N)
       "Proportion of N's that you called N"
   False Positive Rate (FP/N)
       "Proportion of N's that you called P"
   False Negative Rate (FN/P)
       "Proportion of P's that you called N"
   Positive Predictive Value (TP/TP+FP)
       "Proportion of those you called P that are P" (precision in IR)
   Negative Predictive Value (TN/TN+FN)
       "Proportion of those you called N that are N"
   Prevalence (P/A)
       "Proportion of data that are P"
   F-Measure (2 x Rec x Pre / Rec + Pre)
       "Harmonic mean of precision and recall"

--Jettlogic

[edit] Table and edits

See Talk:Sensitivity (tests) re past wish list for simpler description, setting what it is before launching in mathematical jargon. I have also added a table and in Sensitivity (tests) added a worked example. The table is now consistant in Sensitivity, Specificity, PPV & NPV with relevant row or column for calculation highlighted. David Ruben ^Talk 02:44, 11 October 2006 (UTC)