![]() ![]() Advanced Uninstaller PRO will automatically uninstall MedCalc. Confirm the removal by pressing the Uninstall button. Binomial proportion confidence interval on Wikipedia.A way to uninstall MedCalc from your computerThis page contains complete information on how to remove MedCalc for Windows. It is written by MedCalc Software. Take a look here where you can find out more on MedCalc Software. Click on to get more info about MedCalc on MedCalc Software's website. MedCalc is frequently set up in the C:\Program Files\MedCalc directory, however this location can vary a lot depending on the user's decision while installing the program. The full command line for removing MedCalc is MsiExec.exe /Xħ.(Version 22.014 accessed October 30, 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. $$ Accuracy = Sensitivity \times Prevalence + Specificity \times (1 - Prevalence) $$ ![]()
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