Using a Crosstab Query in NVivo

This short video explains the utility of and steps for understanding and using a crosstab query in NVivo  and in version 12 below:


This video tutorial introduces the Crosstab Query in NVivo, explaining its functionality in cross-tabulating different variables and codes. The Crosstab Query allows for the analysis of four dimensions of data and is generally faster than the matrix coding query. The tutorial demonstrates how to perform a Crosstab Query by selecting codes, exploring attitudes or sentiments, and specifying attributes for analysis. The resulting table can be transposed and visually enhanced for better interpretation. The tutorial emphasizes the importance of careful interpretation due to variations in participant numbers across categories.


  • 🔄 Crosstab Query in NVivo:
    • Introduces the Crosstab Query for cross-tabulating variables and codes.
    • Enables analysis of four dimensions of data and is faster than the matrix coding query.
  • 📊 Performing Crosstab Query:
    • Access through the Explorer ribbon, select Queries, and choose Crosstab.
    • Choose whether to crosstab codes against attributes or cases.
    • Specify search criteria, including the selection of codes, attributes, and classification.
  • 👀 Interpreting Results:
    • Transpose the data for better readability.
    • Utilize cell shading to enhance interpretation of attitudes across cases and attributes.
    • Exercise caution in interpreting numbers, especially when participant numbers vary.
  • 📈 Visualization:
    • Explore visualizations, such as charts, for a more comprehensive understanding.
    • Chart options include coding references and coding presence.
    • Charting may require refining the query to manage data volume.
  • 🤔 Interpretation Tips:
    • Demonstration of interpreting specific cell data and exploring text associated with it.
    • Emphasizes the need for careful interpretation due to limitations in participant numbers.
  • 🧐 Data Exploration:
    • Illustrates exploration of attitudes about real estate development across cases, classified by attributes.
    • Highlights the usefulness of Crosstab Query for diving into text with specific variables.
  • 🚀 Query Power:
    • Demonstrates the powerful capabilities of the Crosstab Query for detailed data exploration.
    • Useful for diving into text with specific sets of variables.
  • 📉 Charting Results:
    • Shows the option to visualize results through charts, with examples using economy codes, person case classification, and selected attributes.
    • Provides flexibility in viewing and exporting chart results.
Key Moments
  • Introduction to Crosstab Query00:05
    • Learn about the Crosstab Query in NVivo, a powerful tool for cross-tabulating four dimensions of data.
    • Faster than the matrix coding query, it has a more limited scope but is efficient for specific analyses.
  • Setting up a Crosstab Query02:22
    • Walkthrough on creating a crosstab query, selecting codes, and exploring attitude codes.
    • Demonstration of specifying dimensions, choosing classifications, and preparing to run the query.
  • Interpreting Crosstab Results04:24
    • Understanding the crosstab table, interpreting numbers, and cautioning against overinterpretation.
    • Exploring positive and negative sentiments across different attributes and age groups.
  • Exploring Data Through Crosstab Queries06:09
    • A practical demonstration of the query’s power, diving into specific text with variable sets.
    • Overview of options such as coding references, coding presence, and potential visualizations.