Pay close attention to the data to ensure that you’re not picking up on things that are not there – or obscuring things that are. Thematic analysis is often quite subjective and relies on the researcher’s judgement, so you have to reflect carefully on your own choices and interpretations. However, it also involves the risk of missing nuances in the data. Thematic analysis allows you a lot of flexibility in interpreting the data, and allows you to approach large datasets more easily by sorting them into broad themes. To answer any of these questions, you would collect data from a group of relevant participants and then analyse it.
Thematic analysis is a good approach to research where you’re trying to find out something about people’s views, opinions, knowledge, experiences, or values from a set of qualitative data – for example, interview transcripts, social media profiles, or survey responses. Different approaches to thematic analysis.Probability vs non-probability sampling.
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