Category:QScript Online Library
From Q
The QScript Online Library contains a set of QScripts that can be used directly from Q. These scripts have been written to accomplish tasks that users commonly face in Q, including data checking, data cleaning, generating new variables, generating new tables, and more. These scripts don't need to be modified or saved to your computer.
The scripts are run by selecting Automate > Online Library and selecting a script from the list. QScripts from the QScript Online Library will appear with this icon: 
. In older versions of Q these scripts may be run by selecting Tools > QScripts > Online Library and selecting the script in the menu. This feature is available in Q 4.7 and higher.
The scripts in the Online Library will prompt the user for any information that they require to complete the specified task. For example, if the script makes changes to questions in your project then the user will be shown a list of applicable questions when the script runs.
See also
- QScript Snippets for other examples of QScripts.
- Rule Online Library for a library of rules (which are applied directly to tables and charts).
- JavaScript
- QScript for an overview of the documentation involving JavaScript.
Pages in category ‘QScript Online Library’
The following 142 pages are in this category, out of 142 total.
C
- Choice Modeling - Diagnostic - Class Parameters
- Choice Modeling - Diagnostic - Experimental Design - Balances and Overlaps
- Choice Modeling - Diagnostic - Experimental Design - Numeric Design
- Choice Modeling - Diagnostic - Experimental Design - Standard Errors
- Choice Modeling - Diagnostic - Parameter Statistics
- Choice Modeling - Diagnostic - Posterior Intervals
- Choice Modeling - Diagnostic - Trace Plots
- Choice Modeling - Legacy Choice Modeling - Choice-Based Conjoint (CBC) Setup - JMP
- Choice Modeling - Legacy Choice Modeling - Choice-Based Conjoint (CBC) Setup - Sawtooth CHO Format
- Choice Modeling - Legacy Choice Modeling - Choice-Based Conjoint (CBC) Setup - Sawtooth Dual File Format
- Choice Modeling - Legacy Choice Modeling - Compute Importance
- Choice Modeling - Legacy Choice Modeling - Compute Utilities
- Choice Modeling - Legacy Choice Modeling - Compute Utilities with 0 to 100 Scaling
- Choice Modeling - Legacy Choice Modeling - Compute Within-Attribute Preference Shares (Utilities)
- Choice Modeling - Legacy Choice Modeling - Compute Zero-Centered Diffs (Utilities)
- Choice Modeling - Save Variable(s) - Class Membership Probabilities
- Choice Modeling - Save Variable(s) - Individual-level Coefficients
- Choice Modeling - Save Variable(s) - Membership
- Choice Modeling - Save Variable(s) - Proportion Correct
- Choice Modeling - Save Variable(s) - RLH
- 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)
- Create New Variables - Case-Level Shares
- Create New Variables - Combine Several Questions as a Grid
- Create New Variables - Create New Bottom 2 Category Variables (That is, Bottom 2 Boxes)
- Create New Variables - Create New Bottom 3 Category Variables (That is, Bottom 3 Boxes)
- Create New Variables - Create New Bottom K Category Variables (That is, Bottom K Boxes)
- Create New Variables - Create New Top 2 Category Variables (That is, Top 2 Boxes)
- Create New Variables - Create New Top 3 Category Variables (That is, Top 3 Boxes)
- Create New Variables - Create New Top K Category Variables (That is, Top K Boxes)
- Create New Variables - Create Variables from Merged Categories
- Create New Variables - Flatten
- Create New Variables - Identifying and Removing Outliers
- Create New Variables - Midpoint Coding and Quantification
- Create New Variables - NPS Recoding
- Create New Variables - Rebase Multiple Response Data to NET
- Create New Variables - Standardize Data by Case
- Custom Data Files - Survey Gizmo MaxDiff
D
- Data - Geocode IPs
- Delete tables and plots - Broken tables
- Delete tables and plots - If not significant at a specified level
- Delete tables and plots - If not significant at the 0.001 level (99.9%)
- Delete tables and plots - If not significant at the 0.01 level (99%)
- Delete tables and plots - If not significant at the 0.05 level (95%)
- Delete tables and plots - Remove Tables With Sample Size Lower Than Specified Value
F
H
M
- Marketing - MaxDiff - Analyze as a Ranking Question - Compute Preference Shares from Individual-Level Parameter Means (All Alternatives)
- Marketing - MaxDiff - Analyze as a Ranking Question - Compute Sawtooth-Style Preference Shares from Individual-Level Parameter Means (K Alternatives)
- Marketing - MaxDiff - Analyze as a Ranking Question - Compute Zero-Centered Utilities from Individual-Level Parameter Means (All Alternatives)
- Marketing - MaxDiff - Analyze as a Ranking Question - MaxDiff Setup from an Experimental Design
- Marketing - MaxDiff - Diagnostic - Class Parameters
- Marketing - MaxDiff - Diagnostic - Class Preference Shares
- Marketing - MaxDiff - Diagnostic - Parameter Statistics
- Marketing - MaxDiff - Diagnostic - Posterior Intervals
- Marketing - MaxDiff - Diagnostic - Trace Plots
- Marketing - MaxDiff - Save Variable(s) - Class Membership Probabilities
- Marketing - MaxDiff - Save Variable(s) - Compute Preference Shares
- Marketing - MaxDiff - Save Variable(s) - Compute Sawtooth-Style Preference Shares (K Alternatives)
- Marketing - MaxDiff - Save Variable(s) - Compute Zero-Centered Utilities
- Marketing - MaxDiff - Save Variable(s) - Individual-level Coefficients
- Marketing - MaxDiff - Save Variable(s) - Membership
- Marketing - MaxDiff - Save Variable(s) - Proportion Correct
- Marketing - MaxDiff - Save Variable(s) - RLH
- Marketing - TURF (Total Unduplicated Reach and Frequency)
- Modifying Data - Apply Custom Merges to Scales
- Modifying Data - Create New Bottom K Category NETs (That is, Bottom K Boxes)
- Modifying Data - Create New Top K Category NETs (That is, Top K Boxes)
- Modifying Data - Merge 10 Point Scales Into 3 Categories
- Modifying Data - Merge 7 Point Scales Into 3 Categories
- Modifying Data - Merge and Flatten Scales
- Modifying Data - Merge Categories Less Than or Equal To 0.5%
- Modifying Data - Merge Categories Less Than or Equal To 1%
- Modifying Data - Merge Categories Less Than or Equal To 2%
- Modifying Data - Merge Categories Less Than or Equal To 3%
- Modifying Data - Merge Categories Less Than or Equal To 4%
- Modifying Data - Merge Categories Less Than or Equal To 5%
- Modifying Data - Move the NET to the Top for all Questions
- Modifying Data - Remove Don't Know Categories
- Modifying Data - Use a Question as a Template for Modifying Other Questions
- Modifying Footers - Add Descriptions of Selected Data (e.g., Question name, skips, filtering) From File
- Modifying Labels - Add Variable Names And Values To Labels
- Modifying Labels - Other Specify Categories as Other
- Modifying Labels - Remove Variable Names And Values From Labels
- Modifying Tables or Plots - Number all of the Tables in the Project
- Modifying Tables or Plots - Remove JavaScript from Selected Tables and Plots
- Modifying Tables or Plots - Replacing One Question with Another in All Selected Tables and Plots
- 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 Variables to a New Position
- Multivariate - All Combinations Of Pick Any Categories
P
- Plot/Chart - Bubble Plot from 3 Tables
- Plot/Chart - Scatterplot from 2 Tables
- Preliminary Project Setup - Checking for Errors in Data File Construction
- Preliminary Project Setup - Create Tables for Data Checking
- 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
- Preliminary Project Setup - Search for Improved Question Names in Data Labels
- Preliminary Project Setup - Summary Plots
- Preliminary Project Setup - Summary Tables
R
- Recoding - Midpoint Coding and Quantification
- Recoding - Recoding Higher Values (Capping)
- Recoding - Recoding Lower Values (Capping)
- Recoding - Setting Higher Values to Missing
- Recoding - Setting Lower Values to Missing
- Recoding - Setting the Value of Don't Knows to NaN
- Recoding - Turn Off Missing Data Selection for Specific Values
- Regression - Driver (Importance) Analysis - Beta
- Regression - Driver (Importance) Analysis - Contribution
- Regression - Driver (Importance) Analysis - Elasticity
- Regression - Driver (Importance) Analysis - Kruskal
- Regression - Driver (Importance) Analysis - Linear Regression Coefficients
- Regression - Driver (Importance) Analysis - Relative Importance Analysis
- Regression - Driver (Importance) Analysis - Shapley
