NVivo

A mailing list intended to foster a Community of Practice around the use of NVivo at the University of Calgary. Sign up at https://mailman.ucalgary.ca/mailman/listinfo/nvivo-users-l

Here are links to topics I've been asked about in workshops, but which don't (yet) warrant workshops of their own:

• Other Computer-Assisted Qualitative Data Analysis (CAQDAS) tools
  • Taguette - Open source, also works with Linux
  • RQDA - R package for Qualitative Data Analysis
  • Tropy - basically, NVivo for pictures or photos. A 4-minute overview.
  • Choosing an appropriate CAQDAS package - good reviews of most of the software packages
• Using Software in Qualitative Research: A Step-by-Step Guide  (e-book)
• Visualizations in NVivo
• Importing classification sheets, then manually linking to files or automatically linking to files (YouTube)
• A road map for setting up cases in NVivo .
• Automatic coding by speaker  (formatting styles) (A couple of YouTube videos explain this as well - formatting , then coding )
• Different coding techniques and shortcuts .

Working as part of a team:

• How to set up a master project for research teams (Blog post from Lumivero)
  • YouTube video with the same info .
• Inter-rater reliability testing in NVivo. AKA coding comparison query .
• Inter-rater Reliability in Qualitative Coding: Considerations for its Use (are you doing it because you need to, or because you were told to?)
• An excellent article that describes how inter-rater reliability and the Kappa coefficient are calculated: Inter-rater reliability: the kappa statistic
• Teamworking in stand-alone projects and the merge process (YouTube video from QSR International)
• Merging NVivo Project Files - working in teams (YouTube video from an independent source)

Other resources:

• NVivo 2018 Essential Training on LinkedIn Learning (formerly Lynda.com)
• NVivo YouTube channel
• Lumivero NVivo webinars
• Why should I store my NVivo project on a local drive? Can I store it in a Dropbox, Cloud or on a network?

Anonymising qualitative data

• From the UK Data Service
• From Erasmus University, Rotterdam
• Anonymizer: A framework for text anonymization (Python - very technical)
• Stripping before ChatGPT - De-identifying MS Office Documents (TextWash - somewhat technical, but this is a step-by-step guide)