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These independent analysts also extracted and compared themes.
They then combined their interpretations and compared themes and sub-themes; differences were resolved through consensus.
Authors compared themes to identify commonalities and differences between data generated across the three faith communities.
We have used pseudonyms for participants to demonstrate that we compared themes across dataset, whilst retaining participant anonymity.
We compared themes across cases to ensure that they were both representative and inclusive of all cases.
Authors then characterised, described and agreed on important emerging themes, and compared themes across cases to elucidate commonality and variability.
Similar(51)
Step 5: comparing themes in comments.
These analysts will compare themes and sub-themes until agreement is reached.
We used a method of constant comparison, comparing themes within and between interviews.
This was particularly useful when comparing themes to generic definitions of crisis.
By comparing themes to the naive reading, we strengthened the validity of the analysis.
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CEO of Professional Science Editing for Scientists @ prosciediting.com