Framework Analysis — Framework Method (Ritchie & Spencer)

Both methods identify themes across qualitative data, but Framework Analysis adds a distinctive charting step in which data are entered into a participant-by-theme matrix. This makes cross-case comparison systematic and visible, and creates an explicit audit trail linking every interpretive claim back to a specific source passage. Thematic analysis is more flexible and does not require a matrix; Framework Analysis is more structured and is particularly valuable for team-based or policy-focused research where transparency and comparability are priorities.

Framework Analysis was designed to be pragmatic rather than purely inductive or purely deductive. The thematic framework is built from both the research questions and interview guide (deductive) and themes that emerge during familiarization and indexing (inductive). A purely inductive study — one with no prior questions and an intent to let theory emerge entirely from data — is better served by grounded theory. If your questions are defined in advance but you want room for the data to surprise you, Framework Analysis is well suited.

The analytical matrix can be built in a spreadsheet (Microsoft Excel or Google Sheets) or in a qualitative data analysis package such as NVivo, which has a built-in matrix coding feature. Spreadsheets are widely used in practice because they are accessible to all team members regardless of specialist software training. Whatever tool is used, the critical requirement is that every cell entry retains a reference to the source transcript and line number so the audit trail is maintained.

There is no strict minimum, but the cross-case comparison enabled by the matrix is most useful with samples in the range of 10 to 50 participants. Below about five or six participants the comparative advantage of the matrix is marginal and a case-study or phenomenological design may better serve the research aims. Above 50 participants the charting process becomes very labour-intensive; researchers often work in teams and may focus the matrix on a purposively selected sub-sample.

Yes. Although the method was designed with team contexts in mind, solo researchers use it regularly. The audit trail built into the matrix is equally valuable for a lone analyst — it disciplines the interpretive process and makes it easier to return to the data during write-up. Solo researchers should allow additional time for the charting step, which is the most labour-intensive phase of the analysis.