MedCalc x64 is a complete statistical program for Windows designed to closely match the ... researchers. It is fast, user-friendly and reliable. MedCalc x64 is the most user-friendly software for Receiver ...
MedCalc 16.8User-friendly statistical software
MedCalc is a stand-alone computer program for statistics in the biomedical sciences with an integrated spreadsheet for easy data input. It can import Excel, SPSS, Dbase, Lotus files, and files in SYLK, DIF or text format. Special features of the program are, lots of graphs including ROC curves, Kaplan-Meier survival plots, Bland and Altman plot, Deming and Passing, and Bablok regression for method comparison.
MedCalc 16.8 details
|Released:||Aug 11, 2016|
|File size:||12.95 MB|
|Keywords:||statistic, data, management, science|
MedCalc for Windows 10 - Full description
MedCalc is a complete statistical program for Windows designed to closely match the requirements of biomedical researchers. It is fast, user-friendly and reliable.
MedCalc is the most user-friendly software for Receiver Operating Characteristic curve (ROC curves) analysis. The MedCalc ROC module includes comparison of up to 6 ROC curves.
The software also includes Bland & Altman plot, Passing and Bablok and Deming regression for method comparison studies.
Integrated spreadsheet with 16384 columns and up to 100000 rows.
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 download area).
Complete HTML manual on MedCalc web site.
Context help in dialog boxes.
ROC curve analysis
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 versus criterion values.
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).