Category:Extensions
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This page links to the contents of the extensions available from within Q and Displayr in an upcoming release.
These items can be used in Q or Displayr by selecting any item of the appropriate type specified by any extension. For each applicable extension, a button will appear in the 'Object Inspector', by default on a tab titled 'Actions'.
Pages in category 'Extensions'
The following 111 pages are in this category, out of 111 total.
C
- Choice Modeling - Diagnostic - Class Parameters Table extension
- Choice Modeling - Diagnostic - Experimental Design - Balances and Overlaps of Design extension
- Choice Modeling - Diagnostic - Experimental Design - Numeric Design extension
- Choice Modeling - Diagnostic - Experimental Design - Parameter Standard Errors of Design extension
- Choice Modeling - Diagnostic - Experimental Design - Preview Choice Questionnaire extension
- Choice Modeling - Diagnostic - Parameter Statistics Table extension
- Choice Modeling - Diagnostic - Posterior Intervals Plot extension
- Choice Modeling - Diagnostic - Trace Plots extension
- Choice Modeling - Optimizer
- Choice Modeling - Save Variable(s) - Class Membership
- Choice Modeling - Save Variable(s) - Class Membership Probabilities
- Choice Modeling - Save Variable(s) - Individual-Level Coefficients
- Choice Modeling - Save Variable(s) - Proportion of Correct Predictions
- Choice Modeling - Save Variable(s) - RLH (Root Likelihood)
- Choice Modeling - Save Variable(s) - Utilities (Mean 0)
- Choice Modeling - Save Variable(s) - Utilities (Mean 0, Max Range 100)
- Choice Modeling - Save Variable(s) - Utilities (Mean 0, Mean Range 100)
- Choice Modeling - Save Variable(s) - Utilities (Min 0)
- Choice Modeling - Save Variable(s) - Utilities (Min 0, Max Range 100)
- Choice Modeling - Save Variable(s) - Utilities (Min 0, Mean Range 100)
- Choice Modeling - Simulator
- Choice Modeling - Utilities Plot Extension
- Combo Box (Drop-Down) Filters on an Output
- Create New Variables - Binary Variable(s)
- Create New Variables - Bottom 2 Category Variable(s) (Bottom 2 Boxes)
- Create New Variables - Bottom 3 Category Variable(s) (Bottom 3 Boxes)
- Create New Variables - Bottom K Category Variable(s) (Bottom K Boxes)
- Create New Variables - Case-Level Shares
- Create New Variables - Flatten Question(s)
- Create New Variables - Log Transform Variable(s)
- Create New Variables - Numeric Variable(s) from Code/Category Midpoints
- Create New Variables - Rebase Multiple Response Data in Variable(s) to NET
- Create New Variables - Recode Net Promoter Score (NPS) Variable(s)
- Create New Variables - Scale Variable(s) - Center Within Case
- Create New Variables - Scale Variable(s) - Center Within Variable
- Create New Variables - Scale Variable(s) - Ranks Within Case
- Create New Variables - Scale Variable(s) - Ranks Within Variable
- Create New Variables - Scale Variable(s) - Standardize Within Case
- Create New Variables - Scale Variable(s) - Standardize Within Variable
- Create New Variables - Scale Variable(s) - Unit Interval Within Case
- Create New Variables - Scale Variable(s) - Unit Interval Within Variable
- Create New Variables - Split Grid by Columns
- Create New Variables - Split Grid by Rows
- Create New Variables - Square-Root Variable(s)
- Create New Variables - Top 2 Category Variable(s) (Top 2 Boxes)
- Create New Variables - Top 3 Category Variable(s) (Top 3 Boxes)
- Create New Variables - Top K Category Variable(s) (Top K Boxes)
- Create New Variables - Translate Text
- Create New Variables - Variable(s) with Outliers Removed
D
- Date Filters on an Output
- Dimension Reduction - Diagnostic - Quality Table extension
- Dimension Reduction - Plot - Component Plot Extension
- Dimension Reduction - Plot - Goodness of Fit Plot Extension
- Dimension Reduction - Plot - Scree Plot Extension
- Dimension Reduction - Save Variable(s) - Components/Dimensions
H
M
- Machine Learning - Diagnostic - Model Simulator extension
- Machine Learning - Diagnostic - Prediction-Accuracy Table extension
- Machine Learning - Diagnostic - Table of Discriminant Function Coefficients extension
- Machine Learning - Save Variable(s) - Discriminant Variables
- Machine Learning - Save Variable(s) - Predicted Values
- Machine Learning - Save Variable(s) - Probabilities of Each Response
- Marketing - MaxDiff - Diagnostic - Class Parameters Table extension
- Marketing - MaxDiff - Diagnostic - Class Preference Shares Table extension
- Marketing - MaxDiff - Diagnostic - Parameter Statistics Table extension
- Marketing - MaxDiff - Diagnostic - Posterior Intervals Plot extension
- Marketing - MaxDiff - Diagnostic - Trace Plots extension
- Marketing - MaxDiff - Save Variable(s) - Class Membership
- Marketing - MaxDiff - Save Variable(s) - Class Membership Probabilities
- Marketing - MaxDiff - Save Variable(s) - Individual-Level Coefficients
- Marketing - MaxDiff - Save Variable(s) - Preference Shares
- Marketing - MaxDiff - Save Variable(s) - Proportion of Correct Predictions
- Marketing - MaxDiff - Save Variable(s) - RLH (Root Likelihood)
- Marketing - MaxDiff - Save Variable(s) - Sawtooth-Style Preference Shares (K Alternatives)
- Marketing - MaxDiff - Save Variable(s) - Zero-Centered Utilities
R
- Regression - Diagnostic - Multicollinearity Table (VIF) extension
- Regression - Diagnostic - Plot - Cook's Distance extension
- Regression - Diagnostic - Plot - Cook's Distance vs Leverage extension
- Regression - Diagnostic - Plot - Goodness of Fit extension
- Regression - Diagnostic - Plot - Influence Index extension
- Regression - Diagnostic - Plot - Normal Q-Q extension
- Regression - Diagnostic - Plot - Residuals vs Fitted extension
- Regression - Diagnostic - Plot - Residuals vs Leverage extension
- Regression - Diagnostic - Plot - Scale-Location extension
- Regression - Diagnostic - Prediction-Accuracy Table extension
- Regression - Diagnostic - Test Residual Heteroscedasticity extension
- Regression - Diagnostic - Test Residual Normality (Shapiro-Wilk) extension
- Regression - Diagnostic - Test Residual Serial Correlation (Durbin-Watson) extension
- Regression - Save Variable(s) - Fitted Values
- Regression - Save Variable(s) - Predicted Values
- Regression - Save Variable(s) - Probabilities of Each Response
- Regression - Save Variable(s) - Propensity Weight
- Regression - Save Variable(s) - Residuals
T
- Tables - Unhide Columns
- Tables - Unhide Rows
- Text Analysis - Advanced - Save Variable(s) - Tidied Text
- Text Analysis - Automatic Categorization - Categorize list of items
- Text Analysis - Automatic Categorization - Categorize unstructured text
- Text Analysis - Automatic Categorization - Extract entities
- Text Analysis - Save Variable(s) - Categories
- Text Analysis - Save Variable(s) - First Category
- Text Analysis - Save Variable(s) - Sentiment Scores
- Text Analysis - Sentiment
- Text Box Filters on an Output