I am using purposive sampling to get the data for my study. I have selected the samples based on their field of expertise. How do I know my data is saturated/rich in this case? Do I need to collect a specific minimum number of samples to ensure data richness?
The classic definition of data saturation requires continuing to gather data until you no longer hear anything new. The definition of theoretical or meaning saturation is more subtle, since it requires no longer gaining any insights from the data that you collect (Hennink, Kaiser, & Marconi, 2017).
There a number of relatively recent articles that claim to give numerical estimates for how many interviews it will take to reach data saturation, but they all rely on potentially unrealistic quantitative assumptions. So, I personally do not recommend them.
I agree with Dr. Morgan. Whether you are using a grounded theory approach, a thematic analysis approach or other qualitative approaches, you sequentially keep conducting interviews and generate the codes, main codes/themes etc. for each interviews, up to the point that you find no new main code/theme, which means your data is saturated enough. You cannot/shouldn't apply frequentist assumptions to qualitative research. Sample size is mostly irrelevant in qualitative research.
The issue of saturation is debated in qualitative research. I will conduct as many interviews as needed to gain deeper insight into the problem. When no new ideas emerge with additional interviews then you can end data collection.
Abukari Kwame That would typically be labelled meaning saturation, and it is close to what Grounded Theory calls theoretical saturation.
Thank you so much, Drs, for the answers and clarifications. I hope this thread will help fellow researchers who face the same problem the way it does for me.
Use the principle of saturation as a foundation. This principle involves collecting data until no new themes or patterns emerge from the data1. There are no specific numbers for the sample size needed for saturation or data richness.
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