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 (do not pay extra for the functions you really need).
• compatible with all contemporary Windows desktop editions

MedCalc feature

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

• Complete HTML manual on MedCalc web site.
• Comprehensive context-sensitive help.
• Context help in dialog boxes.

Statistical features

• MedCalc's statistical procedures, tests and graphs
   

  Summary statistics Outlier detection Distribution plots Histogram Cumulative frequency distribution Normal plot Dot plot Box-and-whisker plot Correlation Correlation coefficient Partial correlation Rank correlation Scatter diagram Regression Regression Scatter diagram & regression line Multiple regression Logistic regression Probit regression (Dose-Response analysis) Nonlinear regression T-tests One sample t-test Independent samples t-test Paired samples t-test Rank sum tests Signed rank sum test (one sample) Mann-Whitney test (independent samples) Wilcoxon test (paired samples) Variance ratio test (F-test) Trimmed means Comparison of independent samples (Yuen-Welch test) Paired samples test ANOVA ... One-way analysis of variance Two-way analysis of variance Analysis of covariance Repeated measures analysis of variance Kruskal-Wallis test Friedman test Crosstabs (categorical data) Frequency table & Chi-squared test Fisher's exact test McNemar test Cochran's Q test Relative risk & Odds ratio Cochran–Mantel–Haenszel test Frequencies bar charts Survival analysis Kaplan-Meier survival curves Cox proportional-hazards regression Serial measurements Reference intervals Reference interval Age-related reference interval Method comparison & evaluation Bland-Altman plot Bland-Altman plot with multiple measurements per subject Comparison of multiple methods Mountain plot Deming regression

  Passing & Bablok regression Coefficient of variation from duplicate measurements Agreement & responsiveness Intraclass correlation coefficient Concordance correlation coefficient Inter-rater agreement (kappa) Cronbach's alpha Responsiveness ROC curve analysis ROC curve analysis Interactive dot diagram Plot versus criterion values Plot versus prevalence Predictive values Plot versus prevalence Interval likelihood ratios Comparison of ROC curves Partial area under ROC curve Comparison of partial areas under ROC curves Precision-recall curve Comparison of precision-recall curves Create tables Summary statistics table Correlation table & Correlogram Comparison of independent samples Comparison of paired samples Multiple frequency tables Meta-analysis Introduction Continuous measure Correlation Proportion Relative risk Risk difference Odds ratio Area under ROC curve Generic inverse variance method Tests on summarized data Test for one mean Test for one proportion Chi-squared test Fisher's exact test for a 2x2 table McNemar test on paired proportions Comparison of means (t-test) Comparison of standard deviations (F-test) Comparison of correlation coefficients Comparison of two proportions Comparison of areas under independent ROC curves Confidence interval for a rate Comparison of two rates Relative risk Odds ratio Inter-rater agreement Diagnostic test Likelihood ratios (2xk table) Sample size calculation Single mean Single proportion

  Comparison of two means Paired samples t-test Comparison of two proportions McNemar test Correlation coefficient Survival analysis (logrank test) Bland-Altman plot Area under ROC curve Comparison of two ROC curves Sample size for precision and confidence interval estimation Single mean Single proportion Difference between means Mean difference between paired samples Difference between proportions Difference between paired proportions Coefficient of Variation from duplicate measurements Regression-based reference limits More graphs Data comparison graphs Multiple comparison graphs Clustered multiple comparison graphs Multiple variables graphs Clustered multiple variables graphs Multiple line graph Control chart Youden plot Polar plot Waterfall chart Forest plot Function plot

   

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).

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.
• 150 Mb free space on the hard disk.
• To run MedCalc on a Mac, a Windows emulator is necessary such as Parallels or use Bootcamp

Digimizer 為一個簡單且易上手的圖像測量分析軟體，其功能包括各種影像分析、精準的手動測量、自動物體偵測等。圖片可以是X光圖片或顯微圖等。支援的檔案類型眾多，例如JPG、GIF、 TIFF、BMP、PNG、WMF、EMF與 DICOM，影像可做旋轉，反轉或拉直，也可以調整亮度和對比度 (點選右圖可連結至產品介紹頁面)

特色

Image file operations

• Open, save and print image files
• Acquire image from scanner
• Grab image from live video stream
• Supported file formats: DGZ (native Digimizer file format), JPG, GIF, TIFF, BMP, PNG, WMF, EMF, and DICOM files.

Image manipulation

• Resize
• Crop
• Rotate, flip
• Zoom
• Adjust contrast & brightness
• Contrast auto fix
• Stretch histogram
• Background correction
• Despeckle
• Convert to grayscale
• Convert to color
• Invert
• Negative
• Sharpen
• Filters: Emboss, Arithmetic Mean Filter, Geometric Mean Filter, Harmonic Mean Filter, Median Filter, Maximum Filter, Minimum Filter, Midpoint Filter, Yp Mean Filter

系統需求

System requirements
To use Digimizer, you need a PC with

• Windows Vista, Windows 7, 8, 8.1, 10 or 11.
• 1024 Mb of memory.
• 20 Mb free space on the hard disk.