Emily Namey, R&E Search for Evidence http://researchforevidence.fhi360.org/author/enamey
“The first two posts in this series describe commonly used research sampling strategies and provide some guidance on how to choose from this range of sampling methods. Here we delve further into the sampling world and address sample sizes for qualitative research and evaluation projects. Specifically, we address the often-asked question: How many in-depth interviews/focus groups do I need to conduct for my study?
Within the qualitative literature (and community of practice), the concept of “saturation” – the point when incoming data produce little or no new information – is the well-accepted standard by which sample sizes for qualitative inquiry are determined (Guest et al. 2006; Guest and MacQueen 2008). There’s just one small problem with this: saturation, by definition, can be determined only during or after data analysis. And most of us need to justify our sample sizes (to funders, ethics committees, etc.) before collecting data!
Until relatively recently, researchers and evaluators had to rely on rules of thumb or their personal experiences to estimate how many qualitative data collection events they needed for a study; empirical data to support these sample sizes were virtually non-existent. This began to change a little over a decade ago. Morgan and colleagues (2002) decided to plot (and publish!) the number of new concepts identified in successive interviews across four datasets. They found that nearly no new concepts were found after 20 interviews. Extrapolating from their data, we see that the first five to six in-depth interviews produced the majority of new data, and approximately 80% to 92% of concepts were identified within the first 10 interviews.
Emily’s blog continues here http://researchforevidence.fhi360.org/riddle-me-this-how-many-interviews-or-focus-groups-are-enough
This agrees with our experience of 6-10 samples for FGDs for a project impact evaluation (A couple of additional KIIs would help inform and explain FGD data though). What I wonder is if there should not be any reflection on the size of the project in determining the sample size? If it is spread over a large area with considerable contextual diversity? Nevertheless,these notes together with Emily Namey’s assessment would help us convince some of the donors who favour larger samples disregarding the saturation phenomenon.
Good point about saturation only being discoverable during data analysis, and yes, it’s difficult to get those funding evaluation and research to understand open-ended sample sizes. I wonder if the answer is to plan to do more than you anticipate being necessary, and cut down if you are analysing as you go along (using grounded theory for example). I wrote a little about this in a blog post on saturation: https://www.quirkos.com/blog/post/saturation-qualitative-research-guide but which also touches on a lot of the sample size issues in qualitative research.