2.5

2.5 (10 July 2024)

New features

• Mixed design ANOVA
• Effect size for 80% power is displayed in addition to the 95% power version (thanks to Maja Lebeničnik)
• Brunner-Munzel test instead of Mann-Whitney test (thanks to Maja Lebeničnik)
• Simplified drift-diffusion analysis report
• Work with external editor
  • Ability to open data file with external editor
  • Ability to reload data file automatically when file is saved in the external editor
  • Ability to rerun analyses when data file is reloaded
• Help buttons on dialogs
• New demo data files https://www.crumplab.com/statisticsLab/ (Evelin Haász)
• Python package
  • Results are returned in a dictionary
  • Table results are returned as pandas Stylers
• Continuing support for Spanish localization (Mabel Galai)

Fixes

• Output, localization, and GUI fixes

2.5rc

2.5 (May 2024)

Mac version is not available yet. Check back later for updates about it.

New features

• Brunner-Munzel test instead of Mann-Whitney test (thanks to Maja Lebeničnik)
• Mixed design ANOVA
• Effect size for 80% power is displayed beyond the 95% power version (thanks to Maja Lebeničnik)
• Simplified diffusion analysis report
• Help buttons on dialogs
• Ability to reload data file automatically when file is changed
• Ability to rerun analyses when file is reloaded
• Ability to open data file with external editor
• New demo data files https://www.crumplab.com/statisticsLab/ (Evelin Haász)
• Python package: results are returned in a dictionary
• Continuing support for Spanish localization (Mabel Galai)

Fixes

• Output, localization, and GUI fixes
• Additional fixes since the 2.5beta version

2.5beta

2.5

New features

• Brunner-Munzel test instead of Mann-Whitney test (thanks to Maja Lebeničnik)
• Mixed design ANOVA
• Effect size for 80% power is displayed beyond the 95% power version (thanks to Maja Lebeničnik)
• Simplified diffusion analysis report
• Help buttons on dialogs
• Ability to reload data file automatically when file is changed
• Ability to rerun analyses when file is reloaded
• Ability to open data file with external editor
• New demo data files https://www.crumplab.com/statisticsLab/ (Evelin Haász)
• Python package: results are returned in a dictionary
• Continuing support for Spanish localization (Mabel Galai)

Fixes

• Output, localization, and GUI fixes

2.4.1

2.4.1 (29 October 2023)

Fixes

• Data import fixes

2.4

New features

• Data handling
  • New data view to see the data together with the results (thanks to Belma Bumin)
  • Reload actual data file
  • Multivariate outlier filtering with Mahalanobis distance (Tamás Szűcs)
  • New demo data files https://learningstatisticswithcogstat.com/ (Róbert Fodor)
• Ability to rerun the analyses in the Results pane
• Multiple linear regression analysis (Tamás Szűcs)
  • Scatterplot matrix of raw data
  • Linear regression function
  • Scatterplot with regression line
  • Partial regression plots with regression lines
  • Model fit metrics
  • Partial correlations
  • Residual plot and histogram of residuals
  • Assumptions of inferential statistics
    • Multivariate normality
    • Homoscedasticity
    • Analysis of multicollinearity
  • Population parameter point and interval estimations (including standardized effect sizes)
  • Hypothesis tests
• Reliability analyses (Tamás Szűcs)
  • Internal consistency reliability analysis
    • Item-total scatter plots
    • Cronbach's alpha with and without items and their CIs
    • Item-rest correlation and their CIs
  • Interrater reliability analysis
    • Chart showing scores from different raters
    • ICC values and their CIs
    • Assumption checks for inferential statistics
    • Hypothesis tests whether ICC is 0
• Displaying groups and factors
  • In comparing groups, display groups not only on x-axes but also with colors or in panels
  • In comparing repeated measures variables, display conditions not only on x-axes but also with colors
    • Rearrange the factors flexibly
  • For ordinal repeated measures variables, display the rank of the values
• Comparing variables and groups in mixed design
  • Raw data
  • Descriptives and related charts
  • Parameter estimations and related charts
• Behavioral data diffusion analysis
  • The time unit (sec or msec), error coding (1 or 0), and scaling parameter (0.1 or 1) can be set
  • Slow trials are filtered before the analysis is run
  • Display the number of filtered (missing and slow outlier) trials
  • Number of included trials per conditions are displayed
• Output handling
  • Save results into html file instead of pdf file (Róbert Fodor)
  • Ability to use png or svg image formats for charts (experimental svg support)
• Possibility to print detailed Python error messages to results pane
• New localization
  • Chinese (Xiaomeng Zhu)
  • Malay (Nur Hidayati Miza binti Junaidi)
  • Arabic (Rahmeh Albursan)
• Python package
  • Pandas DataFrames with MultiIndex columns can be imported
  • Diffusion analysis results are returned as pandas Stylers

Fixes

• ⚠️ In outlier filtering, the cases with the limit value will be included and not excluded
• ⚠️ With the update of the scipy module, the p values of the Wilcoxon tests are fixed
• Extended calculation validations (thanks to Eszter Miklós)
• Most settings in Preferences are applied without the need to restart
• Various GUI, and output fixes

2.4

2.4 (12 September 2023)

New features

• Data handling
  • New data view to see the data together with the results (thanks to Belma Bumin)
  • Reload actual data file
  • Multivariate outlier filtering with Mahalanobis distance (Tamás Szűcs)
  • New demo data files https://learningstatisticswithcogstat.com/ (Róbert Fodor)
• Ability to rerun the analyses in the Results pane
• Multiple linear regression analysis (Tamás Szűcs)
  • Scatterplot matrix of raw data
  • Linear regression function
  • Scatterplot with regression line
  • Partial regression plots
    • With regression lines
  • Model fit metrics
  • Partial correlations
  • Residual plot and histogram of residuals
  • Assumptions of inferential statistics
    • Multivariate normality
    • Homoscedasticity
    • Analysis of multicollinearity
  • Population parameter point and interval estimations (including standardized effect sizes)
  • Hypothesis tests
• Reliability analyses (Tamás Szűcs)
  • Internal consistency reliability analysis
    • Item-total scatter plots
    • Cronbach's alpha with and without items and their CIs
    • Item-rest correlation and their CIs
  • Interrater reliability analysis
    • Chart showing scores from different raters
    • ICC values and their CIs
    • Assumption checks for inferential statistics
    • Hypothesis tests whether ICC is 0
• Displaying groups and factors
  • In comparing groups, display groups not only on x-axes but also with colors or in panels
  • In comparing repeated measures variables, display conditions not only on x-axes but also with colors
    • Rearrange the factors flexibly
  • For ordinal repeated measures variables, display the rank of the values
• Comparing variables and groups in mixed design
  • Raw data
  • Descriptives and related charts
  • Parameter estimations and related charts
• Behavioral data diffusion analysis
  • The time unit (sec or msec), error coding (1 or 0), and scaling parameter (0.1 or 1) can be set
  • Slow trials are filtered before the analysis is run
  • Display the number of filtered (missing and slow outlier) trials
  • Number of included trials per conditions are displayed
• Output handling
  • Save results into html file instead of pdf file (Róbert Fodor)
  • Ability to use png or svg image formats for charts (experimental svg support)
• Possibility to print detailed Python error messages to results pane
• New localization
  • Chinese (Xiaomeng Zhu)
  • Malay (Nur Hidayati Miza binti Junaidi)
  • Arabic (Rahmeh Albursan)
• Python package
  • Pandas DataFrames with MultiIndex columns can be imported
  • Diffusion analysis results are returned as pandas Stylers

Fixes

• ⚠️ In outlier filtering, the cases with the limit value will be included and not excluded
• ⚠️ With the update of the scipy module, the p values of the Wilcoxon tests are fixed
• Extended calculation validations (thanks to Eszter Miklós)
• Most settings in Preferences are applied without the need to restart
• Various GUI, and output fixes

2.4rc

New features

• Data handling
  • New data view to see the data together with the results (thanks to Belma Bumin)
  • Reload actual data file
  • Multivariate outlier filtering with Mahalanobis distance (Tamás Szűcs)
  • New demo data files https://learningstatisticswithcogstat.com/ (Róbert Fodor)
• Ability to rerun the analyses in the Results pane
• Multiple linear regression analysis (Tamás Szűcs)
  • Scatterplot matrix of raw data
  • Linear regression function
  • Scatterplot with regression line (feature added after v2.4beta)
  • Partial regression plots
    • With regression lines (feature added after v2.4beta)
  • Model fit metrics
  • Partial correlations
  • Residual plot and histogram of residuals (feature added after v2.4beta)
  • Assumptions of inferential statistics
    • Multivariate normality
    • Homoscedasticity
    • Analysis of multicollinearity
  • Population parameter point and interval estimations (including standardized effect sizes)
  • Hypothesis tests
• Reliability analyses (Tamás Szűcs)
  • Internal consistency reliability analysis
    • Item-total scatter plots
    • Cronbach's alpha with and without items and their CIs
    • Item-rest correlation and their CIs
  • Interrater reliability analysis
    • Chart showing scores from different raters
    • ICC values and their CIs
    • Assumption checks for inferential statistics
    • Hypothesis tests whether ICC is 0
• Displaying groups and factors
  • In comparing groups, display groups not only on x-axes but also with colors or in panels
  • In comparing repeated measures variables, display conditions not only on x-axes but also with colors
    • Rearrange the factors flexibly
  • For ordinal repeated measures variables, display the rank of the values
• Comparing variables and groups in mixed design
  • Raw data
  • Descriptives and related charts
  • Parameter estimations and related charts
• Behavioral data diffusion analysis
  • The time unit (sec or msec), error coding (1 or 0), and scaling parameter (0.1 or 1) can be set
  • Slow trials are filtered before the analysis is run
  • Display the number of filtered (missing and slow outlier) trials
  • Number of included trials per conditions are displayed
• Output handling
  • Save results into html file instead of pdf file (Róbert Fodor)
  • Ability to use png or svg image formats for charts
• Possibility to print detailed Python error messages to results pane
• New localization
  • Chinese (Xiaomeng Zhu)
  • Malay (Nur Hidayati Miza binti Junaidi)
  • Arabic (Rahmeh Albursan)
• Python package (features added after v2.4beta)
  • Pandas DataFrames with MultiIndex columns can be imported
  • Diffusion analysis results are returned as pandas Stylers

Fixes

• ⚠️ In outlier filtering, the cases with the limit value will be included and not excluded
• ⚠️ With the update of the scipy module, the p values of the Wilcoxon tests are fixed
• Extended calculation validations (thanks to Eszter Miklós)
• Most settings in Preferences are applied without the need to restart
• Various GUI, and output fixes

2.4beta

2.4 beta (21 April 2023)

New features

• Data handling
  • New data view to see the data together with the results (thanks to Belma Bumin)
  • Reload actual data file
  • Multivariate outlier filtering with Mahalanobis distance (Tamás Szűcs)
  • New demo data files https://learningstatisticswithcogstat.com/ (Róbert Fodor)
• Ability to rerun the analyses in the Results pane
• Multiple linear regression analysis (Tamás Szűcs)
  • Model fit metrics
  • Partial correlation
  • Partial regression plots
  • Scatterplot matrix of raw data
  • Analysis of multicollinearity
  • Hypothesis tests
• Reliability analyses (Tamás Szűcs)
  • Internal consistency reliability analysis
    • Item-total scatter plots
    • Cronbach's alpha with and without items and their CIs
    • Item-rest correlation and their CIs
  • Interrater reliability analysis
    • Chart showing scores from different raters
    • ICC values and their CIs
    • Assumption checks for inferential statistics
    • Hypothesis tests whether ICC is 0
• Displaying groups and factors
  • In comparing groups, display groups not only on x-axes but also with colors or in panels
  • In comparing repeated measures variables, display conditions not only on x-axes but also with colors
    • Rearrange the factors flexibly
  • For ordinal repeated measures variables, display the rank of the values
• Comparing variables and groups in mixed design
  • Raw data
  • Descriptives and related charts
  • Parameter estimations and related charts
• Behavioral data diffusion analysis
  • The time unit (sec or msec), error coding (1 or 0), and scaling parameter (0.1 or 1) can be set
  • Slow trials are filtered before the analysis is run
  • Display the number of filtered (missing and slow outlier) trials
  • Number of included trials per conditions are displayed
• Output handling
  • Save results into html file instead of pdf file (Róbert Fodor)
  • Ability to use png or svg image formats for charts
• Possibility to print detailed Python error messages to results pane
• New localization
  • Chinese (Xiaomeng Zhu)
  • Malay (Nur Hidayati Miza binti Junaidi)
  • Arabic (Rahmeh Albursan)

Fixes

• ⚠️ In outlier filtering, the cases with the limit value will be included and not excluded
• ⚠️ With the update of the scipy module, the p values of the Wilcoxon tests are fixed
• Extended calculation validations (thanks to Eszter Miklós)
• Most settings in Preferences are applied without the need to restart
• Various GUI, and output fixes

2.3

New features

• Initial support for Bayesian hypothesis tests
  • One sample t-test
  • Pearson correlation
  • Paired two-samples t-test
  • Independent two-samples t-test
• Extended regression analyses (Tamás Szűcs)
  • Residual plot
  • Confidence intervals for regression parameters
  • Population plot with confidence band of regression line
  • ⚠️ Henze-Zirkler test for assumption of multivariate normality
  • White's test and Koenker's test for assumption of homoscedasticity
• Display the filtered cases when filtering outliers
• Post hoc Durbin-Conover test after significant Friedman test
• New localization
  • Turkish (Belma Feride Bumin)

Fixes

• ⚠️ Sensitivity power analysis for Chi-squared test now uses the correct df and makes sure to use w as effect size
• Various GUI, data import, analysis, and output fixes
• Extended calculation validations (thanks to Dóra Hatvani)
• Run from source more simply (thanks to Oliver Lindemann)
• Various usability fixes (thanks to Ádám Szimilkó)
• Mac-specific fixes (Róbert Fodor)

2.3rc

New features

• Initial support for Bayesian hypothesis tests
  • One sample t-test
  • Pearson correlation
  • Paired two-samples t-test
  • Independent two-samples t-test
• Extended regression analyses (Tamás Szűcs)
  • Residual plot
  • Confidence intervals for regression parameters
  • Population plot with confidence band of regression line
  • ⚠️ Henze-Zirkler test for assumption of multivariate normality
  • ⚠️ White's test and Koenker's test for assumption of homoscedasticity
• Display the filtered cases when filtering outliers
• Post hoc Durbin-Conover test after significant Friedman test
• New localization
  • Turkish (Belma Feride Bumin)

Fixes

• Various GUI, data import, analysis, and output fixes
• Extended calculation validations (thanks to Dóra Hatvani)
• Run from source more simply (thanks to Oliver Lindemann)
• Various usability fixes (thanks to Ádám Szimilkó)
• Mac-specific fixes (Róbert Fodor)

2.2

New features

• ⚠️ For outlier filtering, median +- 2.5 * MAD is used instead of using mean +- 2 * SD
• One-way ANOVA's sensitivity power analysis displays eta-square too
• Missing values are excluded from all analyses
  • ⚠️ In Explore variable, relative frequency is calculated without missing cases
  • ⚠️ In Explore variable, population parameter estimations of nominal variable values are calculated without missing cases

Fixes

• Various UI and output fixes
• Missing cases related fixes
  • ⚠️ In Explore variable, Wilcoxon signed-rank test p value is fixed when there are missing cases
  • ⚠️ In Compare repeated measures variables, Hedges'g CI is fixed when there are missing cases
  • ⚠️ In Compare repeated measures variables, CIs are fixed when there are missing cases for more than two nominal variables
  • ⚠️ In Compare groups, the mosaic plots of nominal variables do not show value combinations where other variable value is missing
  • ⚠️ In Compare groups, Cramér's V is fixed when there are missing cases
  • Some statistics were not calculated when there were missing cases