Guidelines for determining nonprobabilistic sample sizes are virtually nonexistent. Purposive samples are the most commonly used form of nonprobabilistic sampling, and their size typically relies on the concept of “saturation,” or the point at which no new information or themes are observed in the data. Although the idea of saturation is helpful at the conceptual level, it provides little practical guidance for estimating sample sizes, prior to data collection, necessary for conducting quality research. Using data from a study involving sixty in-depth interviews with women in two West African countries, the authors systematically document the degree of data saturation and variability over the course of thematic analysis. They operationalize saturation and make evidence-based recommendations regarding nonprobabilistic sample sizes for interviews. Based on the data set, they found that saturation occurred within the first twelve interviews, although basic elements for metathemes were present as early as six...

https://www.rincondepaco.com.mx/rincon/Inicio/Seminario/Documentos/Met_otros/Docs_Dra_Fleiz/Lecturas_sugeridas/Guest_data_saturation_interviews.pdf

How Many Interviews Are Enough?: An Experiment with Data Saturation and Variability

The Foundations of Qualitative Research - Rachel Ormston, Liz Spencer, Matt Barnard, Dawn Snape The Applications of Qualitative Methods to Social Research - Jane Ritchie and Rachel Ormston Design Issues - Jane Lewis and Carol McNaughton Nicholls Ethics of Qualitative Research - Stephen Webster, Jane Lewis and Ashley Brown Designing and Selecting Samples - Jane Ritchie, Jane Lewis, Gilliam Elam, Rosalind Tennant and Nilufer Rahim Designing Fieldwork - Sue Arthur, Martin Mitchell, Jane Lewis and Carol McNaughton Nicholls In-depth Interviews - Alice Yeo, Robin Legard, Jill Keegan, Kit Ward, Carol McNaughton Nicholls and Jane Lewis Focus Groups - Helen Finch, Jane Lewis, and Caroline Turley Observation - Carol McNaughton Nicholls, Lisa Mills and Mehul Kotecha Analysis: Principles and Processes - Liz Spencer, Jane Ritchie, Rachel Ormston, William O'Connor and Matt Barnard Traditions and approaches Analysis in practice - Liz Spencer, Jane Ritchie, William O'Connor, Gareth Morrell and Rachel Ormston Generalisability Writing up qualitative Research - Clarissa White, Kandy Woodfield, Jane Ritchie and Rachel Ormston

/pdf/qualitative-research-practice-a-guide-for-social-science-l4y32se0bj.pdf

Qualitative Research Practice: A Guide for Social Science Students and Researchers

(2000). Determining Validity in Qualitative Inquiry. Theory Into Practice: Vol. 39, Getting Good Qualitative Data to Improve Eduational Practice, pp. 124-130.

Determining Validity in Qualitative Inquiry

A general inductive approach for analysis of qualitative evaluation data is described. The purposes for using an inductive approach are to (a) condense raw textual data into a brief, summary format; (b) establish clear links between the evaluation or research objectives and the summary findings derived from the raw data; and (c) develop a framework of the underlying structure of expe- riences or processes that are evident in the raw data. The general inductive approach provides an easily used and systematic set of procedures for analyzing qualitative data that can produce reliable and valid findings. Although the general inductive approach is not as strong as some other analytic strategies for theory or model development, it does provide a simple, straightforward approach for deriving findings in the context of focused evaluation questions. Many evaluators are likely to find using a general inductive approach less complicated than using other approaches to qualitative data analysis.

/pdf/a-general-inductive-approach-for-analyzing-qualitative-1xoxxy6mp5.pdf

A General Inductive Approach for Analyzing Qualitative Evaluation Data

The rejection of reliability and validity in qualitative inquiry in the 1980s has resulted in an interesting shift for "ensuring rigor" from the investigator’s actions during the course of the research, to the reader or consumer of qualitative inquiry. The emphasis on strategies that are implemented during the research process has been replaced by strategies for evaluating trustworthiness and utility that are implemented once a study is completed. In this article, we argue that reliability and validity remain appropriate concepts for attaining rigor in qualitative research. We argue that qualitative researchers should reclaim responsibility for reliability and validity by implementing verification strategies integral and self-correcting during the conduct of inquiry itself. This ensures the attainment of rigor using strategies inherent within each qualitative design, and moves the responsibility for incorporating and maintaining reliability and validity from external reviewers’ judgements to the investigators themselves. Finally, we make a plea for a return to terminology for ensuring rigor that is used by mainstream science.

/pdf/verification-strategies-for-establishing-reliability-and-2jxdw91v7c.pdf

Verification Strategies for Establishing Reliability and Validity in Qualitative Research

This book explores the philosophical underpinnings, history and key elements of five qualitative inquiry traditions: biography, phenomenology, grounded theory, ethnography and case study. John W Creswell relates research designs to each of the traditions of inquiry and compares each of the research strategies for theoretical frameworks, writing introduction to studies, collecting data, analyzing data, writing the narrative, and employing standards of quality and verifying results. Five journal articles in the appendix offer fascinating reading as well as examples of the five different qualitative designs.

John W. Creswell

Papers

Qualitative inquiry and research design: choosing among five traditions.