Field-based Deviant Case Sampling — Outlier Cases in Naturalistic Field Research
Field-based Deviant Case Sampling · Also known as: field deviant case sampling, outlier case sampling in field research, extreme case sampling in fieldwork, in-situ deviant case sampling
Field-based deviant case sampling is a purposive strategy that deliberately selects cases deviating markedly from an established pattern or norm, with data collected through direct fieldwork — observation, in-situ interviews, and ethnographic engagement — in the participants' natural settings. By studying outliers on-site, researchers gain contextually grounded insight into why and how certain cases diverge from the typical pattern.
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When to use it
Use field-based deviant case sampling when you need to understand why certain cases diverge from a known or expected pattern and when that understanding requires direct, contextually embedded observation — not just distant survey data. It is well-suited to explanatory or hypothesis-generating research in education, public health, organizational studies, community development, and anthropology. It is especially valuable when the deviant cases are geographically or socially accessible for sustained fieldwork. Do not use it when all cases follow the same pattern (no meaningful deviation exists), when fieldwork access is not feasible, when the research question calls for statistical generalization rather than theoretical insight, or when time and resource constraints prevent sustained on-site engagement.
Strengths & limitations
- Contextually grounded data reveal mechanisms behind deviation that surveys or remote instruments cannot capture.
- Deliberate focus on outliers challenges assumptions embedded in typical-case thinking and can generate novel theoretical insights.
- The field-based mode allows real-time probing and observation of deviant processes as they unfold naturally.
- Highly appropriate for theory development, program evaluation, and identifying transferable lessons from exceptional cases.
- Naturalistic setting enhances ecological validity of findings.
- Findings are not statistically generalizable; the deviant case may have idiosyncratic features that limit transferability.
- Fieldwork is resource-intensive in terms of time, travel, and researcher skill in ethnographic or observational methods.
- Identifying a genuinely deviant case requires reliable baseline data; if the norm is poorly characterized, case selection may be arbitrary.
- Researcher presence in the field may alter participant behavior (reactivity), potentially obscuring the very deviation being studied.
- Small number of cases means findings are sensitive to researcher interpretation and may not be replicable.
Frequently asked
How is field-based deviant case sampling different from ordinary deviant case sampling?
The core logic — deliberately selecting cases that deviate from the norm — is the same. The field-based modifier specifies the data collection mode: data are gathered through sustained on-site fieldwork (observation, in-situ interviews, ethnographic engagement) rather than through remote surveys, administrative data extraction, or documentary analysis alone. This distinction matters because fieldwork access, relationship-building, and observational skill become additional methodological requirements.
How many deviant cases should I select?
There is no fixed rule, but one to four cases is common. The criterion is theoretical saturation — the point at which additional deviant cases no longer reveal new mechanisms or contextual factors. Given the resource demands of sustained fieldwork, most studies work with one or two intensively studied deviant cases, sometimes supplemented by briefer comparison visits to typical cases.
How do I establish what counts as deviant?
Define the norm using the best available evidence before entering the field: published benchmarks, administrative datasets, survey data from the broader population, or systematic literature review. Specify a clear quantitative threshold (e.g., outcomes two standard deviations above the mean) or a qualitative criterion (e.g., the only program in a region that retained all staff during a funding crisis). The criterion must be defensible and documented in the methods section.
Can I combine field-based deviant case sampling with other purposive strategies?
Yes. It is common to combine deviant case selection with maximum variation sampling — selecting one outlier at each extreme — or with typical case sampling, where one deviant and one typical case are studied in parallel. Such combinations strengthen comparative analysis and are fully consistent with purposive sampling logic as described by Patton.
Is this method appropriate for quantitative research?
The case-selection logic can inform mixed-methods designs — for example, identifying statistical outliers in a large dataset and then conducting fieldwork at those sites. However, field-based deviant case sampling in its standard form produces qualitative data and serves interpretive or explanatory purposes rather than statistical estimation.
Sources
- Patton, M. Q. (2002). Qualitative Research and Evaluation Methods (3rd ed.). Sage Publications. ISBN: 978-0761919711
- Lincoln, Y. S., & Guba, E. G. (1985). Naturalistic Inquiry. Sage Publications. ISBN: 978-0803924314
How to cite this page
ScholarGate. (2026, June 3). Field-based Deviant Case Sampling. ScholarGate. https://scholargate.app/en/survey-methodology/field-based-deviant-case-sampling
Which method?
Set this method beside its closest kin and read them side by side — the library lays the books on the table; the choice is yours.
- Deviant Case SamplingSurvey Methodology↔ compare
- Maximum Variation SamplingSurvey Methodology↔ compare
- Purposive samplingSurvey Methodology↔ compare
- Snowball SamplingSurvey Methodology↔ compare
- Typical Case SamplingSurvey Methodology↔ compare