Matrices are very powerful for intersecting or cross-tabulating items in your database. This example looks at cross-referencing interviews with a coding scheme to do an in-case-or cross case analysis but you can use matrices to cross-references nodes with each other to check for co-occurrences or to consider nodes with demographic/profiling information from participants or even closed and open questions in a questionnaire. Matrices offer a strategic view of data that you could not get by say, reading through the contents of a code, because they reveal previously unseen patterns in your data.


This video tutorial introduces Matrix Coding Queries in NVivo, which are a basic form of cross-tabulation allowing users to analyze data by different attributes. Matrix coding queries can be used for both quantitative and qualitative analysis, making them useful for surveys and quick data exploration. The tutorial demonstrates how to set up a matrix coding query by selecting data scope, row items, and column items. It also explains how to switch from coding references to words coded for a more detailed analysis. Matrix coding queries can help researchers explore and analyze data in-depth and are not limited to cross-tabulating codes. Additionally, they offer options for adding attribute values and visualizing data using charts.


  • 📊 Matrix Coding Queries in NVivo allow for cross-tabulation analysis.
  • 📈 Useful for both quantitative and qualitative data analysis, including surveys.
  • 📌 Tutorial explains setting up a query by selecting data scope, row items, and column items.
  • 🔄 Switching from coding references to words coded provides more detailed analysis.
  • 🗂 Not limited to cross-tabulating codes; can include different data items.
  • 📊 Options for adding attribute values and visualizing data with charts.
  • 💡 A valuable tool for exploring and analyzing data in research.
Key Moments
  • Introduction to Matrix Coding Queries00:05
    • Overview of Matrix Coding Queries in NVivo.
    • Importance in cross-tabulation for data analysis.
  • Setting Up a Matrix Coding Query00:29
    • Steps to initiate a Matrix Coding Query in NVivo.
    • Choosing scope, adding row and column items.
  • Running a Matrix Coding Query01:55
    • Executing the query and interpreting the results.
    • Demonstrating effective visualization using shading.
  • Understanding Coding References vs. Words Coded03:10
    • Switching from coding references to words coded measure.
    • Highlighting the nuances and importance of interpretation.
  • Exploring Detailed Results04:02
    • Utilizing the power of Matrix Coding Queries to delve into specific overlaps.
    • Example of exploring negative attitude towards jobs and the cost of living.
  • Beyond Cross-Tabulation: Bringing in Different Items04:38
    • Expanding the application to include source files and case classifications.
    • Quick numerical exploration of coding for each interview participant.
  • Visualizing Results and Exporting Data05:27
    • Using the chart tab for visual representations.
    • Considerations for exporting and limitations of numerical expression.
  • Applicability in Research and Conclusion05:49
    • Encouragement to think about the research applications.
    • Acknowledgment of limitations and suitability for large-scale data surveys.