Qualitative research and sampling

In contrast with quantitive research, qualitative research is well-known for its small sample, unstructured or semi-structured techniques. This type of method can provide insights into problem and help idea or hypotheses developments for further quantitive research. Often it does not provide specific variables, or systematic observations. As Kuzel (1992) pointed out, there is no right or wrong between quantitve and qualitative methods. Small but well-chosen cases also deserve their value, especially in clinical and health care area.
However, the assessment quality of qualitative research seems to be a problem (Mays; Pope, 2000). One popular argument maintain that qualitative methods were too subjective. Mays and Pope (2000) suggested that experimenter should focus on “reality” rather than “truth”. In the refinement of method, they suggested study Triangulation (comparing the results from either two or more different methods of data collection), respondent validation (participants’ reactions), clear exposition of methods of data collection and analysis (clear account of data collection and analysis), reflexivity (sensitivity to the method), attention to negative cases (divert case analysis) and fair dealing (incorporation of a wide range of different perspectives).
One important element which might influence assessment quality in qualitative research is sampling. Kuzel (1992) pointed out two important elements: appropriateness and adequacy, in which the former can be fulfilled by (a) consideration of how the sample fits the research purpose and the phenomenon of interest and (b) use of a sampling strategy which is consistent with the style; the later can be fulfilled by (a) selection of sample units serially; (b)continuous adjustment of sample in response to developing categories and interpretations; © sample of the point of saturation of alternative explanations and (d) active search for negative cases or strength.
He also developed a typology categorizing sampling strategies, including Maximum variation, Homogeneous Critical case, Theoretical, confirming/disconfirming, Snowball or chain, Extreme or deviant case, Typical case Intensity, politically important cases, Random purposeful, stratifies purposeful, criterion, Opportunistic, Combination or mixed and Convenience. The form below is the combination of Creswell (1998) and the idea of the author on purposes.

Reference
Kuzel, A. J. (1992). Sampling in qualitative inquiry.
Mays, N., & Pope, C. (2000). Assessing quality in qualitative research. BMJ: British Medical Journal, 320(7226), 50.
Difference between Qualitative Research vs. Quantitative Research. (2017, January 19). Retrieved April 12, 2017, from https://www.snapsurveys.com/blog/what-is-the-difference-between-qualitative-research-and-quantitative-research/
Basic Sampling Strategies: Sample vs. Population Data. (n.d.). Retrieved April 12, 2017, from https://www.isixsigma.com/tools-templates/sampling-data/basic-sampling-strategies-sample-vs-population-data/