IBM SPSS Statistics 29, which is now available for the Swarthmore College community, includes new customer-requested linear ordinary least squares (OLS) regression and parametric accelerated failure time (AFT) model statistical procedures, improved open-source extension integration, UI enhancements, new data visualization features, and other enhancements that are designed to improve everyday usability. Most importantly for Swarthmore folks is that there is a patch for compatibility with MacOS 14 (Sonoma)!
Several Linear OLS alternatives added
The linear elastic net extension procedure estimates regularized linear regression models for a dependent variable on one or more independent variables.
The linear lasso extension estimates L1 loss regularized linear regression models for a dependent variable on one or more independent variables, and includes optional modes to display trace plots and to select the alpha hyperparameter value based on cross validation.
The linear ridge extension procedure estimates L2 or squared loss regularized linear regression models for a dependent variable on one or more independent variables, and includes optional modes to display trace plots and to select the alpha hyperparameter value based on cross validation.
Parametric AFT models
The new procedure invokes the parametric survival models procedure with non-recurrent life time data. Parametric survival models assume that survival time follow a known distribution and this analysis fits accelerated failure time models with their model effects proportional with respect to survival time.
Pseudo-R-squared measures
Pseudo-R-squared measures and the intra-class correlation coefficient are now included in linear mixed models and generalized linear mixed models output when appropriate. The coefficient of determination R2 is a commonly reported statistic, because it represents the proportion of variance explained by a linear model. The intra-class correlation coefficient (ICC) is a related statistic that quantifies the proportion of variance explained by a random grouping factor in multilevel and hierarchical data.
Plotting Enhancements
The Graphboard Template Chooser includes a new violin plot, which is a hybrid of the box and kernel density plots. Violin plots show peaks in the data and are used to visualize the distribution of numerical data. Unlike a box plot that can only show summary statistics, violin plots depict summary statistics and the density of each variable.
Usability improvements
Workbook mode enhancements
Two new workbook toolbar items have been added: Show/Hide all syntax windows and Clear all output. There is also a new button on the status bar to switch between classic (output and syntax) and workbook modes.
Search enhancements
The search feature now provides options for entering terms directly in a toolbar field and for viewing results in a drop-down pane.
Removal of ability to hide unselected cases
Unselected cases are no longer hidden in the data editor when a subset of cases is selected and the unselected cases are not discarded. This represents a return to the behavior of Statistics 27.0.1 and earlier versions.
Python and R upgrades
Furthermore, Python 3.10.4 and R 4.2.0 are also installed with IBM SPSS Statistics 29.
As always, please reach out to ITS for any support questions regarding SPSS and check our KnowledgeBase (https://kb.swarthmore.edu) for important details about installing and using the software tools available to you as a member of the Swarthmore College community.