- MedCalc is a statistical software package for biomedical research.
- Statistics include more than 220 statistical tests, procedures and graphs.
- ROC curve analysis, method comparison and quality control tools.
Easy to learn, fast and reliable
- MedCalc includes more than 220 statistical tests, procedures and graphs
- reference software for ROC curve analysis…
- method comparison and method evaluation including Bland-Altman plot, Passing-Bablok regression, and Deming regression, …
- reference intervals, including age-related reference interval
- Kaplan-Meier survival analysis and Cox proportional-hazards regression
- meta-analysis
- see complete list
- save graphs in SVG, PNG, JPG, high resolution TIF, or other file formats, or as PowerPoint slides (*.pptx).
- free updates
- available with an English, Chinese (simplified and traditional), French, German, Italian, Japanese, Korean, Polish, Portuguese (Brazilian), Russian and Spanish user-interface (help file and documentation in English)
- one edition includes all features
- compatible with all contemporary Windows desktop editions
Data management
- 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.
MedCalc Documentation
- Comprehensive context-sensitive help.
- Complete HTML manual on MedCalc web site.
- Context help in dialog boxes.
- Paperback manual.
Statistical features
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.
Graphs
- 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 SVG, PNG, JPG, GIF, BMP, PCX, or high resolution TIF files, or as PowerPoint slides (*.pptx).
Accessibility
System requirements
- PC with Windows Vista, Windows 7, 8, 8.1, 10 or 11; or Windows Server 2008 or more recent (all 32-bit and 64-bit versions supported).
- On Windows versions prior to Windows 8, support for Excel *.xlsx files additionally requires Microsoft .NET Framework 4.0 (a free download from Microsoft).
- 2048 Mb of memory.
- 60 Mb free space on the hard disk.
- To run MedCalc on a Mac, a Windows emulator is necessary such as Parallels or use Bootcamp.
1. User-Friendly Interface – Designed for medical researchers, it simplifies complex statistical calculations.
2. Comprehensive Statistical Tools – Offers a variety of statistical tests and methods tailored for medical research.
3. Graphical Representation – Provides high-quality graphs and plots for data visualization.
4. Handles Large Datasets – Efficiently processes large amounts of data commonly found in biomedical research.
5. Specialized Medical Research Features – Includes ROC curve analysis, survival analysis, and epidemiological statistics.
6. Automated Reporting – Generates detailed reports, making it easier for researchers to interpret and present their findings.
7. Data Import & Export – Supports various file formats, including Excel, CSV, and SPSS.
1. ROC Curve Analysis – Used in diagnostic testing to evaluate the performance of medical tests.
2. Survival Analysis – Helps in understanding patient survival rates and treatment efficacy.
3. Bland-Altman Analysis – Compares two measurement methods to assess agreement.
4. Regression Analysis – Determines relationships between variables in medical research.
5. Meta-Analysis – Combines results from multiple studies to derive overall conclusions.
6. Epidemiological Studies – Used for risk factor analysis, prevalence studies, and disease association.
7. Clinical Trials – Assists in analyzing treatment effects and patient responses.
MedCalc is particularly beneficial for medical professionals and researchers who need a robust yet easy-to-use tool for statistical analysis in health sciences.
