Usually when we need to check sensitivity and specificity in data. Can you explain it with an example? Can I run this analysis in SPSS?
Classification Assessment Methods
This paper introduces a detailed explanation with numerical examples many classification assessment methods or classification measures such as:
Accuracy, sensitivity, specificity, ROC curve, Precision-Recall curve, AUC score and many other metrics. In this paper, many details about the ROC curve, PR curve, and Detection Error Trade-off (DET) curve. Moreover, many details about some measures which are suitable for imbalanced data are explained.
Your comments are highly appreciated.
https://ac.els-cdn.com/S2210832718301546/1-s2.0-S2210832718301546-main.pdf?_tid=20353999-8c84-422a-8191-fd1059469272&acdnat=1536185805_03b19e159f0675a01f35512961973eb5
Presentation of the paper is here
https://www.researchgate.net/publication/327403649_Classification_assessment_methods_a_detailed_tutorial
Try to read this article
https://academic.oup.com/bjaed/article/8/6/221/406440
The sensitivity of a clinical test refers to the ability of the test to correctly identify those patients with the disease.
The specificity of a clinical test refers to the ability of the test to correctly identify those patients without the disease.
Regarding second part of your question,
I guess you can use SPSS to calculate sensitivity and specificity
Yap! We use Crosstabs in SPSS to determine false negative and false positive tests.
Sensitivity analysis becomes obvious when we use benefit transfer method or when we deal with some conversion factors taken from other studies conducted elsewhere, or we consider a variable that changes invariably. Yes, it can be conducted running any statistical software or package including SPSS, R, Stata etc.
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