patton (1990) purposeful sampling

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Patton, M. (1990). Qualitative evaluation and research methods(pp. 169-186).Beverly Hills, CA: Sage.

Designing Qualitati ve Studies 169

PURPOSEFUL SAMPLING

Perhaps nothing better captures the difference between quantitative

and qualitative methods than the different logics that undergirdsampling approaches. Qualitative inquiry typically focuses in depth onrelatively small samples, even single cases (n = 1), selected purposefully.Quantitative methods typically depend on larger samples selectedrandomly. Not only are the techniques for sampling different, but thevery logic of each approach is unique because the purpose of eachstrategy is different.

The logic and power of probability sampling depends on selecting atruly random and statistically representative sample that will permit

confident generalization from the sample to a larger population. Thepurpose is generalization.

The logic and power of purposeful sampling lies in selecting information-rich cases for study in depth. Information-rich cases are thosefrom which one can learn a great deal about issues of central impor-tance to the purpose of the research, thus the term purposeful sampling.For example, if the purpose of an evaluation is to increase the effec-tiveness of a program in reaching lower-socioeconomic groups, onemay learn a great deal more by focusing in depth on understanding theneeds, interests, and incentives of a small number of carefully selectedpoor families than by gathering standardized information from a large,statistically representative sample of the whole program. The purposeof purposeful sampling is to select information-rich cases whose studywill i lluminate the questions under study.

There are several different strategies for purposefully selectinginformation-rich cases. The logic of each strategy serves a particularevaluation purpose.

(1) Extreme or deviant case sampling. This approach focuses on casesthat are rich in information because they are unusual or special insome way. Unusual or special cases may be particularly troublesome orespecially enlightening, such as outstanding successes or notablefailures. If, for example, the evaluation was aimed at gathering datahelp a national program reach more clients, one might compare a fewproject sites that have long waiting lists with those that have shortwaiting lists. If staff morale was an issue, one might study andcompare high-morale programs to low-morale programs.


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186 QUALITATIVE DESIGNS AND DATA COLLECTION

is to maximize information, the sampling is terminated when no newinformation is forthcoming from new sampled units; thus redundancyis the primary criterion. (emphasis in the original)

This strategy leaves the question of sample size open.

There remains, however, the practical problems of how to negotiatean evaluation budget or how to get a dissertation committee toapprove a design if you don't have some idea of sample size. Samplingto the point of redundancy is an ideal, one that works best for basicresearch, unlimited time lines, and unconstrained resources.

The solution is judgment and negotiation. I recommended thatqualitative sampling designs specify minimum samples based on ex-pected reasonable coverage of the phenomenon given the purpose ofthe study and stakeholder interests. One may add to the sample asfieldwork unfolds. One may change the sample if information emergesthat indicates the value of a change. The design should be understoodto be flexible and emergent. Yet, at the beginning, for planning andbudgetary purposes, one specifies a minimum expected sample sizeand builds a rationale for that minimum, as well as criteria that wouldalert the researcher to inadequacies in the original sampling approach

and/or size.In the end, sample size adequacy, like all aspects of research, is subjectto peer review, consensual validation, and judgment. What is crucial isthat the sampling procedures and decisions be fully described,explained, and justified so that information users and peer reviewershave the appropriate context for judging the sample. The researcher orevaluator is absolutely obligated to discuss how the sample affectedthe findings, the strengths and weaknesses of the sampling procedures,and any other design decisions that are relevant for interpreting and

understanding the reported results. Exercising care not toovergeneralize from purposeful samples, while maximizing to the fullthe advantages of in-depth, purposeful sampling, will do much toalleviate concerns about small sample size.

patton (1990) purposeful sampling

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