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NVivo for Qualitative Research

NVivo Lib Guide is a go-to resource for researchers analyzing qualitative data using NVivo software.


Workflow and Components of NVivo


There are several qualitative methodology styles. A researcher looking for ways to improve health policy or program design might use ‘evaluation methods. NVivo doesn’t favor a particular methodology—it’s designed to facilitate common qualitative techniques no matter what method you use. For example, your files consist of structured, consistently formatted interviews (where each participant is asked the same set of questions). You could autocode the interviews and set up cases for each participant. Then code themes to query and visualize your data.

Basic components of NVivo

  • Sources The primary data you work with in NVivo, including documents, PDFs, datasets, images, audio, and video files.

  • Nodes Thematic codes or categories you create to represent themes, concepts, or ideas emerging from the data. They can be hierarchical, with parent and child nodes.

  • Cases: Units of analysis representing individual instances or subjects, such as people, organizations, or events.

  • Classifications: Categories used to organize cases or nodes based on attributes, which provide additional information or metadata.

  • Attributes: Descriptive variables or properties associated with cases or nodes, such as age, gender, location, or date.

  • Coding: The process of assigning data (e.g., text, images, audio, or video) to nodes or cases, enabling analysis and pattern identification

  • Queries: Tools for exploring and analyzing data in NVivo, including text search, word frequency, coding, matrix coding, and crosstab queries.

  • Framework matrices: Grid-like structures used for summarizing and analyzing qualitative data by cases and themes, allowing for case comparison and pattern identification.

  • Visualization: Graphical representations of data, including charts, maps, cluster analyses, and project maps, which help in identifying patterns, trends, and relationships.

  • Memos: Notes, reflections, or insights created in NVivo to document your thoughts, observations, or interpretations about the data or analysis process.

  • Annotations: Comments or notes linked directly to specific sections of your sources, used to capture ideas or questions about the data.