Source
doi:10.37745/bjmas.2022.0419 — original publication (opens in a new tab; the file is not redistributed)
Context: thesis · No NI feeds (shallow ingest)
Summary
Nyimbili & Nyimbili (2024) review the sixteen types of purposive (purposeful) sampling first codified by Patton (1990) and re-illustrate each with contemporary examples, aimed at helping early-career qualitative researchers select and justify a sampling technique. Purposive sampling deliberately selects information-rich cases that possess the characteristics relevant to the study’s question, rather than seeking statistical representativeness; the authors argue the choice of technique flows from the study’s paradigm and its ontological and epistemological commitments, not from sample size alone. The article catalogues all sixteen techniques (extreme case, deviant case, intensity, maximum variation, homogeneous, typical case, stratified purposeful, critical case, snowball/chain, criterion, theory-based, opportunistic, random purposeful, politically important cases, convenience, and mixed purposeful), notes that even qualitative studies may pair a sample-size formula (Slovin’s formula or an online calculator) with purposive selection provided the choice is justified, and closes on purposive sampling’s core trade-off: handpicking known, characteristic-rich participants yields deep, relevant data but risks bias and compromised credibility. For the thesis it is a methods-support citation for the sampling-strategy section: it supplies the named technique taxonomy and the “when to use which” guidance the study draws on to name and justify its own purposive approach to expert-interview participant selection.
Key thesis insights
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The sixteen purposive-sampling technique types (Patton 1990 typology), each with a one-line “when to use”. (1) Extreme case — the best/most successful cases in the study context; (2) Deviant case — the worst/least successful (the opposite of extreme), to learn from failure; (3) Intensity — information-rich but not extreme cases (e.g. good and poor students), spanning mixed abilities; (4) Maximum variation — participants who share the core characteristic but differ in background/experience, to gain insight from many angles; (5) Homogeneous — regroup the sample into similar-characteristic subgroups, reducing variation and easing group interviewing/analysis; (6) Typical case — average/normal cases, avoiding extremes and deviants; (7) Stratified purposeful — divide into strata to compare between subgroups; (8) Critical case — one pivotal case permitting logical generalisation (“if true here, likely true elsewhere”); (9) Snowball/chain — one relevant participant refers the next until the sample is reached; (10) Criterion — participants must meet a preset criterion; (11) Theory-based — sample manifestations of a theoretical construct, to confirm/disconfirm and deepen analysis; (12) Opportunistic — add participants in-field as new developments emerge; (13) Random purposeful — random selection within a purposeful category when the eligible set is too large (adds credibility, reduces judgement, not for generalisation); (14) Sampling politically important cases — politically aligned/important figures whose input is central; (15) Convenience — handpick nearby/known participants (cheap and fast but credibility is questionable); (16) Mixed purposeful — combine strategies for triangulation and flexibility. LIT_105
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Technique choice follows the study’s purpose and its ontology/epistemology, not sample size alone. “Choices of sampling procedures stem from ontological and epistemological matters” — the researcher first justifies why the chosen unit of analysis (the ‘case’) is relevant and what can be known about the population, then selects a technique that fits the purpose, resources, question and constraints. This is the justification logic the thesis methodology can cite: the sampling technique is derived from the research paradigm and objectives, and must be explicitly reasoned rather than assumed. LIT_105
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The techniques most applicable to an expert-interview qualitative design are criterion, snowball/chain, maximum variation, intensity and mixed purposeful. For a study that recruits knowledgeable informants, criterion sampling (“set a specific criterion which should be followed for participants to take part”) names the eligibility rule; snowball/chain (“one case of interest from people who know … what cases are information rich”) extends a hard-to-reach expert network; maximum variation deliberately spreads across differing backgrounds to surface insight “from as many angles as possible”; intensity keeps cases information-rich without being extreme; and mixed purposeful combines these “to achieve the desired sample … [helping] triangulation … flexibility.” These are the labels the thesis can use to name and defend its own participant-selection procedure. LIT_105
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Purposive sampling’s core trade-off — deep, relevant data versus bias and credibility risk. Its merit is “getting data from the sample you are sure of to provide the best experiences” because participants are handpicked for their relevant knowledge and experience; its demerit is that handpicked, known participants “may give you wrong experiences” or decline to help, and convenience sampling in particular is flagged as “unprofessional … high chances of data manipulation” with “questionable” credibility. A methodology chapter can cite this to acknowledge the limitation and to distance a rigorous purposive design from mere convenience sampling. LIT_105
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Even qualitative studies may pair a sample-size formula with purposive selection — if the choice is justified. The authors note sampling “is never as static as [Patton, 1990] perceived it”: a formula such as Slovin’s (n = N ÷ (1 + Ne²)) or a free online sample-size calculator can draw an initial sample, after which purposive procedures arrive at the actual participants, “what is significant is that the researcher should justify the choice.” Useful supporting point where the thesis needs to reconcile a small purposive qualitative sample with expectations of sample-size reasoning. LIT_105
Notes
- Provenance. Authoritative first-party open-access PDF downloaded directly from the publisher (British Journal of Multidisciplinary and Advanced Studies / European Centre for Research Training and Development UK).
- Identity confirmed against the file. Title, authors (Nyimbili Friday and Nyimbili Leah, lecturers at Chalimbana University, Zambia), journal BJMAS 5(1):90-99 (2024), DOI 10.37745/bjmas.2022.0419, published 16 February 2024 — all match the citation recorded here.
- Cite the primary, use this as the secondary. The 16-type typology is Patton’s (1990, Qualitative Evaluation and Research Methods); this article is a secondary pedagogical exposition of it with contemporary examples. Where the thesis leans on the typology itself, attribute Patton (1990) as the origin and this paper as a recent secondary summary/application.
- data_quality: medium. Low-tier journal with notable typographical and grammatical roughness; examples are illustrative (largely African/education contexts) rather than empirical; the paper restates a well-established framework and reports no original data. Adequate as a methods-support citation, not a primary methodological authority.
- Scope. Thesis-only, with no NI calculation-cell exposure. Read verbatim: the abstract, the introductory sampling discussion, and §2 (the sixteen techniques). No NZ-specific data.
Connections
Referenced by
Concepts (1): Research Methodology
Sources (1): LIT_112