Abstract
<i>Qualitative sampling in the age of Big Data requires tactful negotiation. Although qualitative research aims to explore the depth as opposed to breadth of experiences, opinions, or beliefs of individuals regarding a unique phenomenon, stakeholders or sponsors might not always be convinced that small sample sizes can yield big results. Intimate population awareness, identification of attributes of importance, selection of a purposeful numbers game, and strategic use of instruments can aid in appropriate sampling approaches for large, heterogeneous populations. This paper reviews the principles of nonprobability sampling, summarizes key qualitative sampling characteristics to consider, and provides a set of examples for negotiating sample sizes in the era of Big Data. </i>
Reference47 articles.
1. Ando, H., Cousins, R., & Young, C. (2014). Achieving saturation in thematic analysis: Development and refinement of a codebook. Comprehensive Psychology, 3, Article 4. https://doi.org/10.2466/03.CP.3.4
2. Ary, D., Jacobs, C. L., Irvine, C. K. S., Walker, D. (2018). Introduction to Research in Education. Cengage Learning.
3. Bachman, M. O., O’Brien, M., Husbands, C., Shreeve, A., Jones, N., Watson, J., Reading, R., Thoburn, J., & Mugford, M. (2009). Integrating children’s services in England: National evaluation of children’s trusts. Child: Care, Health and Development, 35(2), 257–265. https://doi.org/10.1111/j.1365-2214.2008.00928.x
4. Baker, S. E., Edwards, R., & Doidge, M. (2012). How many qualitative interviews is enough?: expert voices and early career reflections on sampling and cases in qualitative research. National Centre for Research Methods, Southampton. https://research.brighton.ac.uk/files/301922/how_many_interviews.pdf
5. Banerjee, A., & Chaudhury, S. (2010). Statistics without tears: Populations and samples. Industrial Psychiatry Journal, 19(1), 60–65.