https://manuals.pqstat.pl/ 2026-05-07T19:36:57+00:00 https://manuals.pqstat.pl/ https://manuals.pqstat.pl/lib/tpl/dokuwiki/images/favicon.ico text/html 2022-02-15T16:46:49+00:00 Anonymous (anonymous@undisclosed.example.com) https://manuals.pqstat.pl/en:statpqpl:diagnpl:punktpl Selection of optimum cut-off The point which is looked for is a certain value of the diagnostic variable, which provides the optimum separation of the studied population into to groups: (+) in which the given phenomenon occurs and (--) in which the given phenomenon does not occur. The selection of the optimum cut-off is not easy because it requires specialist knowledge about the topic of the study. For example, different cut-offs will be required in, on the one hand, a test used for screening o… text/html 2022-02-15T16:16:52+00:00 Anonymous (anonymous@undisclosed.example.com) https://manuals.pqstat.pl/en:statpqpl:diagnpl:rocpl The ROC Curve The diagnostic test is used for differentiating objects with a given feature (marked as (+), e.g. ill people) from objects without the feature (marked as (--), e.g. healthy people). For the diagnostic test to be considered valuable, it should yield a relatively small number of wrong classifications. If the test is based on a dichotomous variable then the proper tool for the evaluation of the quality of the test is the analysis of a text/html 2022-02-15T16:46:08+00:00 Anonymous (anonymous@undisclosed.example.com) https://manuals.pqstat.pl/en:statpqpl:diagnpl:rocporpl ROC curves comparison Very often the aim of studies is the comparison of the size of the area under the ROC curve () with the area under another ROC curve (). The ROC curve with a greater area usually allows a more precise classification of objects. Methods for comparing the areas depend on the model of the study. text/html 2022-09-26T23:30:50+00:00 Anonymous (anonymous@undisclosed.example.com) https://manuals.pqstat.pl/en:statpqpl:diagnpl:testpl Evaluation of diagnostic test Suppose that using a diagnostic test we calculate the occurrence of a particular feature (most often disease) and know the gold-standard, so we know that the feature really occurs among the examined people. On the basis of these information, we can build a