Why are some features restricted in Prism? How do I gain access to them?

Restricted features are specific analyses, graphs, or other functionality in Prism that are only available to specific subscription/license plans. The list below includes release versions of Prism along with the restricted features that were introduced in each and the Prism plans that they require.

Prism 11.0.0

Features requiring Prism Pro or Prism Enterprise

• Calculated Variables from In-table Formulas: Write Excel-style formulas to define new variables directly in your Multiple Variables data tables for use downstream in analyses or graphing. Values of calculated variables automatically update when input data or formulas change. Streamline your workflow by eliminating the need for separate transform analysis sheets while maintaining connections to your original data structure.
• Multifactor ANOVA: Handle any factorial design from a single data structure. Run one-way, two-way, three-way, or N-way ordinary ANOVA from the Multiple Variables tables without restructuring your data. Add or remove factors as needed, define your model with main effects, two-way and three-way interactions, and perform multiple comparisons tests for even more meaningful results.
• Classic Analyses from Multiple Variables Data Tables: Perform t tests, nonlinear regression, and Kaplan-Meier survival analysis directly from Multiple Variables tables without restructuring your data. For nonlinear regression and survival analysis, analyze multiple response variables simultaneously by defining your response, predictor, and grouping variables: Prism will handle the rest.
• Enhanced Effect Size Reporting: New effect size metrics for ANOVA (eta squared, partial eta squared, Cohen's f), contingency table analyses (the Phi coefficient and Cramér's V), and t tests (Cohen's d, Hedges' g, and Glass's Δ) for more comprehensive statistical reporting.

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Prism 10.6.0

Features requiring Prism Pro or Prism Enterprise

• Automatic Cluster Number Selection for K-means clustering: A set of 17 methods and associated metrics calculated automatically. Each metric determines an "optimal" number of clusters for the given data/analysis, and a consensus value is determined by comparing the optimal number of clusters across all metrics. This optimal cluster number is reported and used by Prism 

Features requiring Prism Standard

• Improved Title Controls for Magic: Rather than updating the all three of the X axis, Y axis, and Graph Titles in the target graph to match the source graph, Prism's Magic feature now allows you to specify each of these titles individually. If you want the X axis title in the target graph to update, but to leave the Y axis title and Graph title unchanged, now you can!

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Prism 10.5.0

Features requiring Prism Pro or Prism Enterprise

• Automatic number at risk table: When performing Kaplan-Meier survival analysis, Prism will automatically generate a table aligned with the graph of the survival curves. This table displays the number of subjects at risk (as well as optionally the cumulative number of subjects censored) at each time point on the X axis of the corresponding graph, and will automatically update if the range/interval of this axis changes.

Features requiring Prism Standard

• Multiple (pairwise) comparisons for Kaplan-Meier survival analysis: Specify which pairs of survival curves you'd like to compare, and Prism will provide all of the details for each comparison in a new tab of analysis results.
• Axis variable assignment controls: when creating a multiple variables graph, these controls found in the Graph Inspector panel allow you to select a desired variable to assign to the X or Y axis, or to quickly toggle through all available variables for these axes
• Increasing the number of decimal places for graph axis labels: when creating a graph with numeric labels, you can choose to display up to a maximum number of 14 decimal places.

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Prism 10.4.0

Features requiring Prism Pro or Prism Enterprise

• Integration with Dotmatics Luma: Make the most of your data and results from Prism through our new integration with Dotmatics Luma, a Scientific Intelligence Platform designed to streamline research with AI-driven, adaptive workflows and seamless data integration.

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Prism 10.3.0

Features requiring Prism Pro or Prism Enterprise

• Hierarchical clustering: Uncover the natural connections between observations in your data. This machine learning technique allows you to investigate how closely different observations are related to each other and uncover groupings within your data.
• K-means clustering: Specify a target number of clusters, and this machine learning algorithm will partition your data, iteratively grouping the most similar observations together and adjusting cluster assignments.
• Dendrograms: Visualize the hierarchical relationships from clustering analyses. Use dendrograms as an independent graph or as part of a heatmap from the output of hierarchical clustering.
• Heat maps from multiple variables data: define categorical X-axis and Y-axis variables along with a continuous metric variable to be displayed in the two-dimensional visualization. Alternatively, treat your multiple variables data table as a matrix, and plot the values of the table on the heat map using the rows and columns as the axis variables.
• Confidence ellipses and convex hulls: Visually represent estimates for the parameters that define the population from which your data were drawn, or clearly indicate the boundaries for groups of data on your graphs.

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