MedCalc screenshot

MedCalc is a powerful statistical software package designed specifically for biomedical research and clinical applications. Renowned for its user-friendly interface and extensive range of features, MedCalc supports detailed data analysis, from basic descriptive statistics to complex multivariate analyses.

Here’s an in-depth look at its features and capabilities:

Data Management:

MedCalc offers robust data management tools to facilitate efficient and accurate data handling:

Integrated Spreadsheet: Supports up to 1,048,576 rows and 16,384 columns, providing ample space for large datasets.

Handling Missing Data: Automatically manages missing data to ensure the integrity of your analyses.

Outlier Management: Easily exclude outliers to refine your dataset.

WYSIWYG Text Editor: Built-in editor for creating and editing text within the software.

Data Import: Import data from Excel (including Excel 2007), SPSS, DBase, Lotus, SYLK, DIF, or plain text formats.

Subgroup Analysis: Easily select and analyze specific subgroups within your dataset.

MedCalc Documentation:

Comprehensive documentation and help resources are readily available:

HTML Manual: Detailed manual available on the MedCalc website.

Context-Sensitive Help: Extensive help available within the software, including context help in dialog boxes.

Statistical Features:

MedCalc includes a wide array of statistical procedures designed to meet the needs of biomedical researchers:

Descriptive Statistics: Generate detailed summaries, including mean, median, standard deviation, and range.

Hypothesis Testing: Conduct t-tests, ANOVA, correlation, and regression analyses.

Survival Analysis: Perform Kaplan-Meier survival curves, log-rank tests, and Cox proportional hazards models.

Meta-Analysis: Combine results from multiple studies with fixed-effect and random-effects models.

ROC Curve Analysis:

MedCalc is a leading software for ROC curve analysis, providing comprehensive tools for evaluating diagnostic tests:

AUC Calculation: Calculate the Area Under the Curve (AUC) with standard error, 95% confidence interval, and P-value, using methodologies from DeLong et al. (1988) and Hanley & McNeil (1982, 1983).

Sensitivity and Specificity: List sensitivity, specificity, likelihood ratios, and predictive values for all threshold values.

Interactive Threshold Selection: Choose threshold values in an interactive dot diagram with automatic calculation of sensitivity and specificity.

Graphical Analysis: Plot sensitivity and specificity or cost versus criterion values, and predictive values versus prevalence.

Comparison of ROC Curves: Compare up to six ROC curves, including difference in AUC with standard error, 95% confidence interval, and P-value.

Sample Size Calculation: Determine the required sample size for ROC curve analysis.


MedCalc offers extensive graphing capabilities to visualize your data and analysis results:

Graph Gallery: A wide variety of graph types to choose from.

Data Point Identification: Identify specific data points within graphs.

Annotation Tools: Add text boxes, lines, arrows, and connectors.

Graph Management: Name, save, and recall graphs and associated statistics.

Export Options: Save graphs as SVG, PNG, JPG, GIF, BMP, PCX, high-resolution TIF files, or PowerPoint slides.


Automate your analyses with scripting:

Batch Processing: Run multiple statistical procedures with a single command, saving time and ensuring consistency.


MedCalc is designed with accessibility in mind, ensuring usability for all users.

System Requirements:

To run MedCalc, the following system specifications are recommended:

Operating System: Windows Vista, Windows 7, 8, 8.1, 10, or 11; Windows Server 2008 or newer (32-bit and 64-bit versions supported).

Memory: 2048 MB of RAM.

Disk Space: 100 MB of free disk space.

Additional Requirements: On Windows versions prior to Windows 8, support for Excel *.xlsx files requires Microsoft .NET Framework 4.0.

Mac Compatibility: Requires a Windows emulator such as Parallels or Bootcamp to run on a Mac.

MedCalc stands out as an essential tool for biomedical researchers, providing a comprehensive suite of statistical analysis tools, excellent data management capabilities, and powerful ROC curve analysis. Its user-friendly design, extensive documentation, and accessibility make it a valuable asset for conducting high-quality research.

MedCalc - Changelog:

Added Inter-Item and Item-Total correlation in Cronbach's alpha.

Added the confidence intervals for the regression coefficients in multiple regression.

Fixed a bug that could hide the standard error of the constant in multiple regression.

MedCalc now allows the X-axis of a histogram to be changed after it has been created.

In Variable properties, added the possibility to mark a variable as categorical and select a reference category (such as used in Logistic regression and Cox proportional-hazards regression).

Some bug fixes.

Download MedCalc:

For windows 32 bit:

Size: 33.29 MB - Download

For windows 64 bit:

Size: 35.97 MB - Download