This article describes how to use a built-in QScript to scan through a data file and look for data that likely needs to be examined or corrected. The script creates tables with cells highlighted that may be of interest.
Requirements
A data file loaded in Q
Method
To run this QScript, select Automate > Browse Online Library > Preliminary Project Setup > Tables for Data Checking.
The QScript examines all tables containing non-text and non-date data, and:
- Identifies all tables containing cells with sample sizes of less than 30.
- Identifies all tables containing 'Don't know' responses.
- Identifies all tables containing blank labels.
- Identifies all tables containing options chosen by 5 or fewer people, or, less than 1% of respondents.
- Identifies all empty tables.
- Identifies numeric data containing outliers, where a variable contains values that are more than or less than 3 standard deviations above or below the mean
- Identifies questions where the Base n is not the same for all variables.
Identified tables have the relevant cells highlighted in yellow (via Rules or Table JavaScript in earlier versions of Q). Data containing outliers will be shown as histograms.
Next
How to Use Scripts to Automate Data Checking and Cleaning
How to Check for Errors in Data File Construction
How to Identify Questions with Straight-Lining/Flat-Lining
How to Create New Variable(s) with Outliers Removed
How to Hide Uninteresting Data
How to Remove Truncated Text from Variable Labels
How to Reverse Scales in Questions