On-premise statistics tool that assist biomedical researchers with ROC curve analysis, method comparison and meta-analysis.
- Integrated spreadsheet with 1 048 576 rows and 16 384 columns.
- Correct handling of missing data.
- Outliers can easily be excluded.
- Built-in WYSIWYG text editor.
- Imports Excel, Excel 2007, SPSS, DBase and Lotus files, and files in SYLK, DIF or plain text format.
- Easy selection of subgroups for statistical analysis.
- Comprehensive help file.
- Manual in PDF format (go to dowrnload area).
- Complete HTML manual on MedCalc web site.
- Context help in dialog boxes.
ROC curve analysis
MedCalc is the reference software for ROC curve analysis. Our ROC curve analysis module includes:
- Area under the curve (AUC) with standard error, 95% confidence interval, P-value. Offers choice between methodology of DeLong et al. (1988) and Hanley & McNeil (1982, 1983).
- List of sensitivity, specificity, likelihood ratios, and positive and negative predictive values for all possible threshold values.
- ROC curve graph with 95% Confidence Bounds.
- Threshold values can be selected in an interactive dot diagram with automatic calculation of corresponding sensitivity and specificity.
- Plot of sensitivity and specificity, or cost, versus criterion values.
- Plot of predictive values versus prevalence.
- Interval likelihood ratios.
- Comparison of up to 6 ROC curves: difference between the areas under the ROC curves, with standard error, 95% confidence interval and P-value.
- Sample size calculation for area under ROC curve and comparison of ROC curves.
- Go to the ROC curve analysis section of the MedCalc manual for more information on ROC curve analysis in MedCalc.
- Lots of graphs, see Graph gallery.
- Data point identification in graphs.
- Draw text boxes, lines, arrows and connectors.
- Name, save and recall graphs and statistics.
- Statistical info in graph windows.
- Save graphs as BMP, PNG, GIF, PCX, JPG or TIF files, or as PowerPoint slides (*.pptx).