Qualitative Sampling Essay ⋆ Sociology Essay Examples ⋆ EssayEmpire

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Perhaps nothing better captures the difference between quantitative and qualitative methods than the different logics that undergird sampling approaches. Qualitative inquiry typically focuses in depth on relatively small samples, even single cases (n = 1), selected purposefully. Quantitative methods typically depend on larger samples selected randomly. Not only are the techniques for sampling different, but also the very logic of each approach is unique because the purpose of each strategy is different.

The logic and power of random sampling derives from statistical probability theory. In contrast, the logic and power of purposive sampling lies in selecting information-rich cases for study in depth. Information-rich cases are those from which one can learn a great deal about issues of central importance to the purpose of the inquiry, thus the term purposive sampling (or alternatively, purposeful sampling). What would be ”bias” in statistical sampling, and therefore a weakness, becomes intended focus in qualitative sampling, and therefore a strength. Studying information-rich cases yields insights and in-depth understanding rather than empirical generalizations. For example, if the purpose of a program evaluation is to increase the effectiveness of a program in reaching lower-socioeconomic groups, one may learn a great deal more by studying in depth a small number of carefully selected poor families than by gathering standardized information from a large, statistically representative sample of the whole program. Purposive sampling focuses on selecting information-rich cases whose study will illuminate the questions under study. There are several different strategies for purposefully selecting information-rich cases. The logic of each strategy serves a particular purpose. Only one strategy is reviewed here.

Extreme or deviant case sampling involves selecting cases that are information-rich because they are unusual or special in some way, such as outstanding successes or notable failures. In the early days of AIDS research when HIV infections almost always resulted in death, a small number of cases of people infected with HIV who did not develop AIDS became crucial outlier cases that provided important insights into directions researchers should take in combating AIDS. In program evaluation, the logic of extreme-case sampling is that lessons may be learned from successes and failures that are relevant to improving more typical programs. Consider a national program with hundreds of local sites. Many programs are operating adequately based on reports from knowledgeable sources who have made site visits to enough programs to know what the variation is. But a few programs verge on being disasters and others are excelling. If one wanted to document precisely the natural variation among programs, a random sample would be appropriate, one of sufficient size to be representative and permit generalizations to the total population of programs. However, with limited resources and time, and with the priority being how to improve programs, an evaluator might learn more by intensively studying one or more examples of really poor programs and one or more examples of really excellent programs. The evaluation focus then becomes a question of understanding under what conditions programs get into trouble and under what conditions programs exemplify excellence. The researchers and intended users involved in the study think through what cases they could learn the most from and those are the cases that are selected for study.

Bibliography:

Bernard, H. R. (2000) Social research methods: qualitative and quantitative approaches. Sage, Thousand Oaks, CA.
Denzin, N. & Lincoln, Y. (eds.) (2000) Handbook of Qualitative Research, 2nd edn. Sage, Thousand Oaks, CA.
Patton, M. Q (2002) Qualitative Research and Evaluation Methods, 3rd edn. Sage, Thousand Oaks, CA.