Category:Displayr - Anything Menu
		
		
		
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List of scripts that appear in the Anything menu in Displayr.
Pages in category "Displayr - Anything Menu"
The following 200 pages are in this category, out of 288 total.
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C
- Calculation - First
 - Calculation - Last
 - Choice Modeling - Compare Models
 - Choice Modeling - Convert Alchemer (Survey Gizmo) Conjoint Data for Analysis
 - Choice Modeling - Diagnostic - Class Parameters Table
 - Choice Modeling - Diagnostic - Experimental Design - Balances and Overlaps of Design
 - Choice Modeling - Diagnostic - Experimental Design - Numeric Design
 - Choice Modeling - Diagnostic - Experimental Design - Parameter Standard Errors of Design
 - Choice Modeling - Diagnostic - Parameter Statistics Table
 - Choice Modeling - Diagnostic - Posterior Intervals Plot
 - Choice Modeling - Diagnostic - Trace Plots
 - Choice Modeling - Ensemble of Models
 - Choice Modeling - Experimental Design
 - Choice Modeling - Export Design To Qualtrics
 - Choice Modeling - Hierarchical Bayes
 - Choice Modeling - Latent Class Analysis
 - Choice Modeling - Multinomial Logit
 - Choice Modeling - Optimizer
 - Choice Modeling - Preview Choice Questionnaire
 - 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
 - Combo Box (Drop-Down) Filters on an Output
 - Correlation - Correlation Matrix
 - Correlation - Distance Matrix
 - Correlation - Scatterplot Matrix
 - 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 - Combine Questions as a Grid
 - 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 - 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
- Data - Countries from IP Address(es) (Geocoding)
 - Data - Google Trends
 - Data - Sample Size Description
 - Data - Stack
 - Data - Stock Prices
 - Delete Tables and Plots - Delete If Broken
 - Delete Tables and Plots - Delete If Not Significant at Specified Level
 - Delete Tables and Plots - Delete If Not Significant at the 0.001 Level (99.9%)
 - Delete Tables and Plots - Delete If Not Significant at the 0.01 Level (99%)
 - Delete Tables and Plots - Delete If Not Significant at the 0.05 Level (95%)
 - Delete Tables and Plots - Delete If Sample Size Lower Than Specified Value
 - Dimension Reduction - Correspondence Analysis of a Square Table
 - Dimension Reduction - Correspondence Analysis of a Table
 - Dimension Reduction - Diagnostic - Component Plot
 - Dimension Reduction - Diagnostic - Goodness of Fit Plot
 - Dimension Reduction - Diagnostic - Moonplot
 - Dimension Reduction - Diagnostic - Quality Table
 - Dimension Reduction - Diagnostic - Scree Plot
 - Dimension Reduction - Dimension Reduction Scatterplot
 - Dimension Reduction - Multidimensional Scaling (MDS)
 - Dimension Reduction - Multiple Correspondence Analysis
 - Dimension Reduction - Principal Components Analysis
 - Dimension Reduction - Principal Components Analysis Biplot
 - Dimension Reduction - Save Variable(s) - Components/Dimensions
 - Dimension Reduction - t-SNE
 
F
M
- Machine Learning - Classification And Regression Trees (CART)
 - Machine Learning - Compare Models
 - Machine Learning - Deep Learning
 - Machine Learning - Diagnostic - Prediction-Accuracy Table
 - Machine Learning - Diagnostic - Table of Discriminant Function Coefficients
 - Machine Learning - Ensemble of Models
 - Machine Learning - Gradient Boosting
 - Machine Learning - Linear Discriminant Analysis
 - Machine Learning - Random Forest
 - Machine Learning - Save Variable(s) - Discriminant Variables
 - Machine Learning - Save Variable(s) - Predicted Values
 - Machine Learning - Save Variable(s) - Probabilities of Each Response
 - Machine Learning - Support Vector Machine
 - Marketing - Brand Health Table
 - Marketing - MaxDiff - Compare Models
 - Marketing - MaxDiff - Convert Alchemer (Survey Gizmo) MaxDiff Data for Analysis
 - Marketing - MaxDiff - Diagnostic - Class Parameters Table
 - Marketing - MaxDiff - Diagnostic - Class Preference Shares Table
 - Marketing - MaxDiff - Diagnostic - Parameter Statistics Table
 - Marketing - MaxDiff - Diagnostic - Posterior Intervals Plot
 - Marketing - MaxDiff - Diagnostic - Trace Plots
 - Marketing - MaxDiff - Ensemble of Models
 - Marketing - MaxDiff - Experimental Design
 - Marketing - MaxDiff - Hierarchical Bayes
 - Marketing - MaxDiff - Latent Class Analysis
 - Marketing - MaxDiff - Multinomial Logit
 - 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
 - Marketing - MaxDiff - Varying Coefficients
 - Marketing - Price Sensitivity Meter
 - Missing Data - Little's MCAR Test
 - Missing Data - Plot by Case
 - Missing Data - Plot of Patterns
 - Missing Data - Save Variable(s) - Filter for Complete Cases
 - Modify Data - Add Bottom K Category NETs (Bottom K Boxes)
 - Modify Data - Add Top K Category NETs (Top K Boxes)
 - Modify Data - Merge Categories of Size 0.5% or Less
 - Modify Data - Merge Categories of Size 1% or Less
 - Modify Data - Merge Categories of Size 2% or Less
 - Modify Data - Merge Categories of Size 3% or Less
 - Modify Data - Merge Categories of Size 4% or Less
 - Modify Data - Merge Categories of Size 5% or Less
 - Modify Data - Remove Don't Know Categories
 - Modify Labels - Relabel Other/Specify Categories as Other
 - Move Data - Move All Filters to the Top
 - Move Data - Move All Hidden Questions to the Bottom
 - Move Data - Move All Weights to the Top
 - Move Data - Move Variable Set(s) Down One Row
 - Move Data - Move Variable Set(s) to Bottom
 - Move Data - Move Variable Set(s) to Top
 - Move Data - Move Variable Set(s) Up One Row
 
P
- Preliminary Project Setup - Check for Errors in Data File Construction
 - Preliminary Project Setup - Hide Uninteresting Data
 - Preliminary Project Setup - Identify Questions with Straight-Lining/Flat-Lining
 - Preliminary Project Setup - Remove Truncated Text from Variable Labels
 - Preliminary Project Setup - Reverse Scales in Question(s)
 - Preliminary Project Setup - Suggest Better Question Names from Source Labels
 - Preliminary Project Setup - Summary Plots
 - Preliminary Project Setup - Summary Tables
 - Preliminary Project Setup - Tables for Data Checking
 
R
- Recode - Recode High Values (Capping) in Numeric Variable(s)
 - Recode - Recode Low Values (Capping) in Numeric Variable(s)
 - Recode - Recode Variable(s) Using Code/Category Midpoints
 - Recode - Set High Values to Missing in Numeric Variable(s)
 - Recode - Set Low Values to Missing in Numeric Variable(s)
 - Recode - Set Value of Don't Knows to NaN
 - Recode - Turn Off Missing Data Selection for Specific Values
 - Regression - Binary Logit
 - Regression - Diagnostic - Multicollinearity Table (VIF)
 - Regression - Diagnostic - Plot - Cook's Distance
 - Regression - Diagnostic - Plot - Cook's Distance vs Leverage
 - Regression - Diagnostic - Plot - Goodness of Fit
 - Regression - Diagnostic - Plot - Influence Index
 - Regression - Diagnostic - Plot - Normal Q-Q
 - Regression - Diagnostic - Plot - Residuals vs Fitted
 - Regression - Diagnostic - Plot - Residuals vs Leverage
 - Regression - Diagnostic - Plot - Scale-Location
 - Regression - Diagnostic - Prediction-Accuracy Table
 - Regression - Diagnostic - Test Residual Heteroscedasticity
 - Regression - Diagnostic - Test Residual Normality (Shapiro-Wilk)
 - Regression - Diagnostic - Test Residual Serial Correlation (Durbin-Watson)
 - Regression - Driver Analysis
 - Regression - Generalized Linear Model
 - Regression - Linear Regression
 - Regression - Multinomial Logit
 - Regression - NBD Regression
 - Regression - Ordered Logit
 - Regression - Poisson Regression
 - Regression - Quasi-Poisson Regression
 - Regression - Save Variable(s) - Fitted Values
 - Regression - Save Variable(s) - Predicted Values
 - Regression - Save Variable(s) - Probabilities of Each Response
 - Regression - Save Variable(s) - Residuals
 - Regression - Stepwise