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Comment
. 2023 Jun;18(4):1239-1241.
doi: 10.1007/s11739-023-03247-2. Epub 2023 Mar 8.

Beware the IBM SPSS statistics® in multiple ROC curves analysis

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Comment

Beware the IBM SPSS statistics® in multiple ROC curves analysis

Ahmad Sabry Saleh. Intern Emerg Med. 2023 Jun.
No abstract available

Keywords: COVID-19; Prognosis; ROC curve; Statistics.

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Conflict of interest statement

The author declares that he has no known competing financial interests or personal relationships that could have influenced the work reported in this paper.

Figures

Fig. 1
Fig. 1
The IBM SPSS statistics “ROC Curve: Options” dialog. In the “Test Direction” area, the user must choose which direction is positive. Only curves with similar direction of association can be displayed properly in the same plot
Fig. 2
Fig. 2
ROC curves depicted by three statistical software for ferritin and lymphocytes which have different direction of association with mortality in patients with COVID-19. A larger value in ferritin indicates a positive test result (mortality) while a smaller value in lymphocytes indicates a positive test result (mortality). Curves are displayed properly in the same plot when depicted by Analyze-it® (A) and MedCalc® (B) with AUCs of 0.775 and 0.789, respectively. However, the IBM SPSS Statistics® (using the default test direction entry; “Larger test result indicates more positive test”) displayed the lymphocytes curve below the diagonal reference line with misleadingly small AUC of 0.211 (C). Transformation of lymphocytes (via multiplying all values by − 1) displayed the two curves properly in the same plot (D). Dataset analyzed includes 266 COVID-19 patients with paired measurements of ferritin and lymphocytes (online resource 1)  from reference [4]; an open access article distributed under the terms of the Creative Commons Attribution License

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