MedCalc is the reference software for ROC curve analysis. Imports Excel, Excel 2007, SPSS, DBase and Lotus files, and files in SYLK, DIF or plain text format.Įasy selection of subgroups for statistical analysis.Ĭomplete HTML manual on MedCalc web site. Integrated spreadsheet with 1?048?576 rows and 16?384 columns. The software also includes Bland & Altman Description, Passing and Bablok and Deming regression for method comparison studies. The MedCalc ROC module includes comparison of up to 6 ROC curves. MedCalc is the most user-friendly software for Receiver Operating Characteristic curve (ROC curves) analysis. MedCalc is a complete statistical program for Windows designed to closely match the requirements of biomedical researchers. Binomial proportion confidence interval on Wikipedia.Free Download MedCalc 22.012 Multilingual Free Download | 52.3 Mb.(Version 22.014 accessed November 2, 2023) See also Zweig MH, Campbell G (1993) Receiver-operating characteristic (ROC) plots: a fundamental evaluation tool in clinical medicine.Zhou XH, NA Obuchowski, DK McClish (2002) Statistical methods in diagnostic medicine.Metz CE (1978) Basic principles of ROC analysis.Mercaldo ND, Lau KF, Zhou XH (2007) Confidence intervals for predictive values with an emphasis to case-control studies.Hanley JA, McNeil BJ (1982) The meaning and use of the area under a receiver operating characteristic (ROC) curve.Griner PF, Mayewski RJ, Mushlin AI, Greenland P (1981) Selection and interpretation of diagnostic tests and procedures.Gardner IA, Greiner M (2006) Receiver-operating characteristic curves and likelihood ratios: improvements over traditional methods for the evaluation and application of veterinary clinical pathology tests.Altman DG, Machin D, Bryant TN, Gardner MJ (Eds) (2000) Statistics with confidence, 2 nd ed.

2007 except when the predicitive value is 0 or 100%, in which case a Clopper-Pearson confidence interval is reported. 2000.Ĭonfidence intervals for the predictive values are the standard logit confidence intervals given by Mercaldo et al. Sensitivity, specificity, disease prevalence, positive and negative predictive value as well as accuracy are expressed as percentages.Ĭonfidence intervals for sensitivity, specificity and accuracy are 'exact' Clopper-Pearson confidence intervals.Ĭonfidence intervals for the likelihood ratios are calculated using the 'Log method' as given on page 109 of Altman et al.

$$ Accuracy = Sensitivity imes Prevalence + Specificity imes (1 - Prevalence) $$

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