Saturation Analysis for Interview Study

As part of this study:

"Minimizing Threats Through Responsible Voluntary Confidential Food Safety Data Sharing: Insights from Food Industry Leaders"

By Linda Kalunga, Katherine Koebel, Carrie Alexander, Martin Wiedmann, Aaron Smith, Aaron Adalja, Renata Ivanek

Preprint: https://doi.org/10.21203/rs.3.rs-6960610/v1

This repository contains code used to conduct a saturation analysis for a qualitative interview study. The analysis includes:

• A sequential saturation curve
• A comparison of code emergence in actual vs. randomized interview order
• A bootstrap analysis to assess impact of interview order on ssaturation points

Overview

The goal of this analysis was to assess saturation in the data comprising of 65 codes across 27 interview transcripts

Files

• 'saturation_analysis.ipynb' - Main notebook contaning the full code used in the analysis
• 'S3. Binary_coded_matrix_data' - Input data

Requirements

This code was developed in Google Colab (https.//colab.research.google.com), which comes pre-installed with necessary packages, including:

• NumPy
• pandas
• matplotlib

To use Google Colab, you will need a Google account to open, run, and save notebooks. To run this code locally, make sure you have the above packages installed