Framework Analysis is a qualitative research method that involves organizing and analyzing data using a predefined analytical framework. The analytical framework is a set of predetermined themes or categories that are derived from the research questions or objectives. The framework provides a structured approach to data analysis and can help to identify patterns, themes, and relationships in the data. Here are the general steps in Framework Analysis:
1. Familiarization: Get familiar with the data by reading and re-reading it.
2. Identify a Coding Framework: Identify a coding framework or set of themes that will be used to analyze the data.
3. Coding: Code the data by applying the coding framework to the data.
4. Charting: Chart or summarize the data by creating tables or matrices that display the distribution and frequency of each theme or category across the data set.
5. Mapping and interpretation: Analyze the data by examining the relationship between different themes or categories, and by exploring the implications and meanings of the findings in relation to the research question.
6. Verification: Verify the accuracy and validity of the findings by checking them against the original data, comparing them with other sources of data, and seeking feedback from others.
7. Reporting: Report the findings by presenting them in a clear, concise, and organized manner.
Framework Analysis is a systematic and structured approach to data analysis that emphasizes transparency and replicability. It is an inherently comparative form of thematic analysis which employs an organized structure of inductively- and deductively-derived themes (i.e., a framework) to conduct cross-sectional analysis using a combination of data description and abstraction. Framework Analysis can be used in various fields such as business, healthcare, and social sciences.