Porovnat metody
Prohlédněte si vybrané metody vedle sebe; řádky, které se liší, jsou zvýrazněny.
| Terénní výběr maximální variace× | Účelový výběr – výběr případů na základě kritérií× | |
|---|---|---|
| Obor | Metodologie dotazníkových šetření | Metodologie dotazníkových šetření |
| Rodina | Process / pipeline | Process / pipeline |
| Rok vzniku≠ | 1990 (Patton); field application established through ecological and ethnographic practice in the 1990s–2000s | Formalized ~1980–1990 |
| Tvůrce≠ | Michael Quinn Patton (maximum variation sampling); adapted for field research contexts | Michael Quinn Patton (systematic articulation); roots in early qualitative inquiry |
| Typ≠ | Purposive qualitative/mixed-methods sampling strategy | Non-probability sampling strategy |
| Původní zdroj≠ | Patton, M. Q. (2002). Qualitative Research and Evaluation Methods (3rd ed.). Sage. [Maximum variation sampling discussed in Chapter 5] ISBN: 978-0761919711 | Patton, M. Q. (1990). Qualitative Evaluation and Research Methods (2nd ed.). Sage. ISBN: 978-0803937796 |
| Další názvy | field MVS, field-based purposeful maximum variation, maximum heterogeneity field sampling, diverse case field sampling | judgmental sampling, selective sampling, criterion-based sampling, purposeful sampling |
| Příbuzné≠ | 6 | 4 |
| Shrnutí≠ | Field-based maximum variation sampling is a purposive strategy in which a researcher deliberately selects field sites, ecological plots, communities, or observational units that span the widest possible range of relevant characteristics. By maximising heterogeneity among selected units, the approach ensures that both common patterns shared across diverse conditions and unique features specific to particular contexts are documented, making findings robust across a broad spectrum of real-world variation. | Purposive sampling is a non-probability strategy in which the researcher deliberately selects participants, documents, or cases that are information-rich with respect to the research question. Rather than drawing units at random, the researcher applies explicit criteria aligned with the study's purpose, maximising the depth and relevance of the data collected. It is the default sampling logic in most qualitative research designs and is also used in mixed-methods and applied evaluative work. |
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