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Statistical software for biomedical research with a rich set of functions, graph types and an advanced module for performing ROC graph analysis. MedCalc is designed to meet the requirements of biomedical researchers with respect to the statistical analysis of large datasets. It provides the necessary tools and features for performing Receiver Operating Characteristic curve analysis, data plotting, Bablok and Deming regression and more.

With an integrated spreadsheet with over 100,000 rows, MedCalc is capable of reading and displaying detailed data imported from Excel, SPSS, Dbase, Lotus or extracted from SYLK, DIF or text files. The information can be easily sorted, filtered or edited.
The built-in data browser offers a comfortable means of easily managing data, variables, notes, texts and graphs, while the array of supported graphs and diagrams (scatter plots, method comparison graphs, graphs for subgroups or for up to 24 continuous variables, survival curves, serial measurement, standardized mean plots and many more) make it perfect for analyzing trends and comparing information.
One of the most important features of MedCalc is related to its ROC curve analysis capabilities. It can generate the ROC curve graph with 95% confidence bounds, calculate specificity, sensitivity, predictive values for all the thresholds, likelihood ratios, generate conclusive plots and determine the size of an area under the ROC graph. Up to 6 ROC curves can be compared, calculating the differences between the areas, the standard errors, P-values and more.
MedCalc is capable of handling missing data, creating subgroups, calculating percentile ranks and power transformation. It features outlier detection, correlation and regression tools, Bland & Altman plotting, while also enabling you to run Anova, variance ratio, mean, propertion, Chi-Square, Fisher and T-tests.
A summary of the statistical report can be easily generated and data can be placed and viewed side-by-side thanks to the multiple comparison graphs function.
MedCalc requires at least basic statistics knowledge in order to get the most out of its potential. Its extensive array of features make it a must-have tool for running method comparison studies and analyzing biomedical data.

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https://www.medcalc.org/history.php

System requirements: 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).

️ MedCalc 23.3.4 Multilingual (74.57 MB) (74.57 MB)
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Statistical software for biomedical research with a rich set of functions, graph types and an advanced module for performing ROC graph analysis. MedCalc is designed to meet the requirements of biomedical researchers with respect to the statistical analysis of large datasets. It provides the necessary tools and features for performing Receiver Operating Characteristic curve analysis, data plotting, Bablok and Deming regression and more.

With an integrated spreadsheet with over 100,000 rows, MedCalc is capable of reading and displaying detailed data imported from Excel, SPSS, Dbase, Lotus or extracted from SYLK, DIF or text files. The information can be easily sorted, filtered or edited.

The built-in data browser offers a comfortable means of easily managing data, variables, notes, texts and graphs, while the array of supported graphs and diagrams (scatter plots, method comparison graphs, graphs for subgroups or for up to 24 continuous variables, survival curves, serial measurement, standardized mean plots and many more) make it perfect for analyzing trends and comparing information.

One of the most important features of MedCalc is related to its ROC curve analysis capabilities. It can generate the ROC curve graph with 95% confidence bounds, calculate specificity, sensitivity, predictive values for all the thresholds, likelihood ratios, generate conclusive plots and determine the size of an area under the ROC graph. Up to 6 ROC curves can be compared, calculating the differences between the areas, the standard errors, P-values and more.

MedCalc is capable of handling missing data, creating subgroups, calculating percentile ranks and power transformation. It features outlier detection, correlation and regression tools, Bland & Altman plotting, while also enabling you to run Anova, variance ratio, mean, propertion, Chi-Square, Fisher and T-tests.

A summary of the statistical report can be easily generated and data can be placed and viewed side-by-side thanks to the multiple comparison graphs function.
MedCalc requires at least basic statistics knowledge in order to get the most out of its potential. Its extensive array of features make it a must-have tool for running method comparison studies and analyzing biomedical data.

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https://www.medcalc.org/history.php

️ MedCalc 23.3.1 Multilingual (75.07 MB)
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Statistical software for biomedical research with a rich set of functions, graph types and an advanced module for performing ROC graph analysis. MedCalc is designed to meet the requirements of biomedical researchers with respect to the statistical analysis of large datasets. It provides the necessary tools and features for performing Receiver Operating Characteristic curve analysis, data plotting, Bablok and Deming regression and more.

With an integrated spreadsheet with over 100,000 rows, MedCalc is capable of reading and displaying detailed data imported from Excel, SPSS, Dbase, Lotus or extracted from SYLK, DIF or text files. The information can be easily sorted, filtered or edited.

The built-in data browser offers a comfortable means of easily managing data, variables, notes, texts and graphs, while the array of supported graphs and diagrams (scatter plots, method comparison graphs, graphs for subgroups or for up to 24 continuous variables, survival curves, serial measurement, standardized mean plots and many more) make it perfect for analyzing trends and comparing information.

One of the most important features of MedCalc is related to its ROC curve analysis capabilities. It can generate the ROC curve graph with 95% confidence bounds, calculate specificity, sensitivity, predictive values for all the thresholds, likelihood ratios, generate conclusive plots and determine the size of an area under the ROC graph. Up to 6 ROC curves can be compared, calculating the differences between the areas, the standard errors, P-values and more.

MedCalc is capable of handling missing data, creating subgroups, calculating percentile ranks and power transformation. It features outlier detection, correlation and regression tools, Bland & Altman plotting, while also enabling you to run Anova, variance ratio, mean, propertion, Chi-Square, Fisher and T-tests.

A summary of the statistical report can be easily generated and data can be placed and viewed side-by-side thanks to the multiple comparison graphs function.
MedCalc requires at least basic statistics knowledge in order to get the most out of its potential. Its extensive array of features make it a must-have tool for running method comparison studies and analyzing biomedical data.

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https://www.medcalc.org/history.php

️ Medcalc 23.2.8 Multilingual (75.33 MB)
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Statistical software for biomedical research with a rich set of functions, graph types and an advanced module for performing ROC graph analysis. MedCalc is designed to meet the requirements of biomedical researchers with respect to the statistical analysis of large datasets. It provides the necessary tools and features for performing Receiver Operating Characteristic curve analysis, data plotting, Bablok and Deming regression and more.

With an integrated spreadsheet with over 100,000 rows, MedCalc is capable of reading and displaying detailed data imported from Excel, SPSS, Dbase, Lotus or extracted from SYLK, DIF or text files. The information can be easily sorted, filtered or edited.

The built-in data browser offers a comfortable means of easily managing data, variables, notes, texts and graphs, while the array of supported graphs and diagrams (scatter plots, method comparison graphs, graphs for subgroups or for up to 24 continuous variables, survival curves, serial measurement, standardized mean plots and many more) make it perfect for analyzing trends and comparing information.

One of the most important features of MedCalc is related to its ROC curve analysis capabilities. It can generate the ROC curve graph with 95% confidence bounds, calculate specificity, sensitivity, predictive values for all the thresholds, likelihood ratios, generate conclusive plots and determine the size of an area under the ROC graph. Up to 6 ROC curves can be compared, calculating the differences between the areas, the standard errors, P-values and more.

MedCalc is capable of handling missing data, creating subgroups, calculating percentile ranks and power transformation. It features outlier detection, correlation and regression tools, Bland & Altman plotting, while also enabling you to run Anova, variance ratio, mean, propertion, Chi-Square, Fisher and T-tests.

A summary of the statistical report can be easily generated and data can be placed and viewed side-by-side thanks to the multiple comparison graphs function.
MedCalc requires at least basic statistics knowledge in order to get the most out of its potential. Its extensive array of features make it a must-have tool for running method comparison studies and analyzing biomedical data.

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https://www.medcalc.org/history.php

️ Medcalc 23.2.7 Multilingual (70.77 MB)

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Statistical software for biomedical research with a rich set of functions, graph types and an advanced module for performing ROC graph analysis. MedCalc is designed to meet the requirements of biomedical researchers with respect to the statistical analysis of large data sets. It provides the necessary tools and features for performing Receiver Operating Characteristic curve analysis, data plotting, Bablok and Deming regression and more.

With an integrated spreadsheet with over 100,000 rows, MedCalc is capable of reading and displaying detailed data imported from Excel, SPSS, Dbase, Lotus or extracted from SYLK, DIF or text files. The information can be easily sorted, filtered or edited.

The built-in data browser offers a comfortable means of easily managing data, variables, notes, texts and graphs, while the array of supported graphs and diagrams (scatter plots, method comparison graphs, graphs for subgroups or for up to 24 continuous variables, survival curves, serial measurement, standardized mean plots and many more) make it perfect for analyzing trends and comparing information.

One of the most important features of MedCalc is related to its ROC curve analysis capabilities. It can generate the ROC curve graph with 95% confidence bounds, calculate specificity, sensitivity, predictive values for all the thresholds, likelihood ratios, generate conclusive plots and determine the size of an area under the ROC graph. Up to 6 ROC curves can be compared, calculating the differences between the areas, the standard errors, P-values and more.

MedCalc is capable of handling missing data, creating subgroups, calculating percentile ranks and power transformation. It features outlier detection, correlation and regression tools, Bland & Altman plotting, while also enabling you to run Anova, variance ratio, mean, propertion, Chi-Square, Fisher and T-tests.
A summary of the statistical report can be easily generated and data can be placed and viewed side-by-side thanks to the multiple comparison graphs function.
MedCalc requires at least basic statistics knowledge in order to get the most out of its potential. Its extensive array of features make it a must-have tool for running method comparison studies and analyzing biomedical data.

️ MedCalc 23.2.6 Multilingual (70.78 MB)

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Statistical software for biomedical research with a rich set of functions, graph types and an advanced module for performing ROC graph analysis. MedCalc is designed to meet the requirements of biomedical researchers with respect to the statistical analysis of large datasets. It provides the necessary tools and features for performing Receiver Operating Characteristic curve analysis, data plotting, Bablok and Deming regression and more.

With an integrated spreadsheet with over 100,000 rows, MedCalc is capable of reading and displaying detailed data imported from Excel, SPSS, Dbase, Lotus or extracted from SYLK, DIF or text files. The information can be easily sorted, filtered or edited.
The built-in data browser offers a comfortable means of easily managing data, variables, notes, texts and graphs, while the array of supported graphs and diagrams (scatter plots, method comparison graphs, graphs for subgroups or for up to 24 continuous variables, survival curves, serial measurement, standardized mean plots and many more) make it perfect for analyzing trends and comparing information.
One of the most important features of MedCalc is related to its ROC curve analysis capabilities. It can generate the ROC curve graph with 95% confidence bounds, calculate specificity, sensitivity, predictive values for all the thresholds, likelihood ratios, generate conclusive plots and determine the size of an area under the ROC graph. Up to 6 ROC curves can be compared, calculating the differences between the areas, the standard errors, P-values and more.
MedCalc is capable of handling missing data, creating subgroups, calculating percentile ranks and power transformation. It features outlier detection, correlation and regression tools, Bland & Altman plotting, while also enabling you to run Anova, variance ratio, mean, propertion, Chi-Square, Fisher and T-tests.
A summary of the statistical report can be easily generated and data can be placed and viewed side-by-side thanks to the multiple comparison graphs function.
MedCalc requires at least basic statistics knowledge in order to get the most out of its potential. Its extensive array of features make it a must-have tool for running method comparison studies and analyzing biomedical data.

Code:Copy to clipboard

https://www.medcalc.org/history.php

System requirements: 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).

️ MedCalc 22.3.3 Multilingual (74.58 MB) (74.58 MB)
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Statistical software for biomedical research with a rich set of functions, graph types and an advanced module for performing ROC graph analysis. MedCalc is designed to meet the requirements of biomedical researchers with respect to the statistical analysis of large datasets. It provides the necessary tools and features for performing Receiver Operating Characteristic curve analysis, data plotting, Bablok and Deming regression and more.

With an integrated spreadsheet with over 100,000 rows, MedCalc is capable of reading and displaying detailed data imported from Excel, SPSS, Dbase, Lotus or extracted from SYLK, DIF or text files. The information can be easily sorted, filtered or edited.

The built-in data browser offers a comfortable means of easily managing data, variables, notes, texts and graphs, while the array of supported graphs and diagrams (scatter plots, method comparison graphs, graphs for subgroups or for up to 24 continuous variables, survival curves, serial measurement, standardized mean plots and many more) make it perfect for analyzing trends and comparing information.

One of the most important features of MedCalc is related to its ROC curve analysis capabilities. It can generate the ROC curve graph with 95% confidence bounds, calculate specificity, sensitivity, predictive values for all the thresholds, likelihood ratios, generate conclusive plots and determine the size of an area under the ROC graph. Up to 6 ROC curves can be compared, calculating the differences between the areas, the standard errors, P-values and more.

MedCalc is capable of handling missing data, creating subgroups, calculating percentile ranks and power transformation. It features outlier detection, correlation and regression tools, Bland & Altman plotting, while also enabling you to run Anova, variance ratio, mean, propertion, Chi-Square, Fisher and T-tests.

A summary of the statistical report can be easily generated and data can be placed and viewed side-by-side thanks to the multiple comparison graphs function.
MedCalc requires at least basic statistics knowledge in order to get the most out of its potential. Its extensive array of features make it a must-have tool for running method comparison studies and analyzing biomedical data.

Code:Copy to clipboard

https://www.medcalc.org/history.php

System requirements: 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).

️ MedCalc 22.3.2 Multilingual (74.59 MB) (74.59 MB)
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Mecway is a comprehensive user friendly finite element analysis package for Windows with a focus on mechanical and thermal simulation such as stress analysis, vibration and heat flow. It is inexpensive and has an intuitive graphical interface for easy mesh creation and display of solutions.

Powerful
Dynamic, static, thermal, buckling, acoustic, etc.
Full nonlinear capability though seamless integration with the included CalculiX solver
Wide range of element, load and material types
Both manual and automatic meshing tools
Up to 1,000,000 nodes
CAD associativity

Easy
Very quick learning curve
Instant feedback on errors as you work
Modern Windows interface
Visualize your models both graphically and in an outline tree
Units aware

Accurate
Verification examples with hand calculations
25 years of development history

What’s New
official site does not provide any info about changes in this version.

️ Mecway 28.0 (x64) – (232 MB)
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MDB Viewer Plus is a small, yet highly reliable utility designed to open and manipulate Access files. By providing such simple means to view, edit and search MDB and Accdb database records, it’s an easy alternative to Microsoft Access.

MDB Viewer Plus Feature List
Can open MDB and Accdb files.
Table opening, viewing and inline editing.
Tabbed interface.
Standard search and partial word search.
Filtering / sorting records by fields.
Table and query result printing.
Record view (form style view).
Record count.
Query – standard SQL select statements.
Opening and saving of SQL statements to file.
Table Info (field types) plus printing of structure.
Table types.
Portable; no installation required to run. (Provided MDAC is already installed as part of Windows)
Exports to TXT, HTML, XML, DBF, XLS, WKS, RTF and PDF.
Import from CSV,TXT,Doc,XLS,WK1,WQ1,SAV,DB,DBF,MDB,ADO,ADT,DAT,HTM,XML,WAB and VCS.
Support Access 2007 Accdb files (Provided "Microsoft Office Access database engine 2007" is installed).
Unicode compatible.
Create new blank database.
Create / rename / delete table.
Set / change / remove password.
Support for Workgroup Files (MDW).
Display related child table link to the parent table.
Add / remove / rename / alter fields.
Customisable many to many relationship dialog.
Selective opening of tables

️ MDB Viewer Plus 2.72 (1.74 MB)

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