Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Целенаправленный отбор проб на основе анализа чувствительности× | Отбор по отклоняющимся случаям× | |
|---|---|---|
| Область | Методология опросов | Методология опросов |
| Семейство | Process / pipeline | Process / pipeline |
| Год появления≠ | 1990s–2000s | 1990 |
| Автор метода≠ | Rooted in Patton's purposive sampling typology; sensitivity analysis practices formalized in research synthesis literature | Michael Quinn Patton |
| Тип≠ | Purposive qualitative sampling with robustness verification | Purposive qualitative sampling strategy |
| Основополагающий источник≠ | Patton, M. Q. (2015). Qualitative Research and Evaluation Methods (4th ed.). Sage Publications. ISBN: 978-1412972123 | Patton, M. Q. (2002). Qualitative Research and Evaluation Methods (3rd ed.). Sage Publications. ISBN: 978-0761919711 |
| Другие названия≠ | purposive sampling with sensitivity checks, robust purposive sampling, sensitivity-tested purposive selection | extreme case sampling, outlier sampling, negative case sampling, deviant-case selection |
| Связанные | 5 | 5 |
| Сводка≠ | Sensitivity analysis-based purposive sampling extends conventional purposive sampling by systematically testing whether key findings or case-selection decisions change when the inclusion criteria, selection logic, or boundary conditions are altered. It applies the logic of sensitivity analysis — standard in quantitative research and systematic reviews — to qualitative case selection, giving researchers explicit evidence of how robust their purposive choices are to plausible alternative selection rules. | Deviant case sampling is a purposive qualitative sampling strategy in which the researcher intentionally selects cases that are unusual, exceptional, or markedly different from the norm — outliers, extreme successes, or conspicuous failures. The goal is not statistical representation but deep learning from cases that illuminate the boundaries of a phenomenon, challenge prevailing assumptions, or reveal processes that typical cases obscure. |
| ScholarGateНабор данных ↗ |
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