Comparer des méthodes

	Échantillonnage théorique basé sur le terrain	Échantillonnage à variation maximale	Échantillonnage raisonné
Domaine	Méthodologie d'enquête	Méthodologie d'enquête	Méthodologie d'enquête
Famille	Process / pipeline	Process / pipeline	Process / pipeline
Année d'origine	1967	1985 (Lincoln & Guba); elaborated 1990–2002 (Patton)	Formalized ~1980–1990
Auteur d'origine	Barney G. Glaser and Anselm L. Strauss	Lincoln & Guba; systematised by Michael Quinn Patton	Michael Quinn Patton (systematic articulation); roots in early qualitative inquiry
Type	Qualitative iterative sampling strategy	Purposive qualitative sampling strategy	Non-probability sampling strategy
Source fondatrice	Glaser, B. G., & Strauss, A. L. (1967). The Discovery of Grounded Theory: Strategies for Qualitative Research. Aldine. ISBN: 978-0202302607	Patton, M. Q. (2002). Qualitative Research and Evaluation Methods (3rd ed.). Sage. Chapter 5: Purposeful Sampling. ISBN: 978-0761919711	Patton, M. Q. (1990). Qualitative Evaluation and Research Methods (2nd ed.). Sage. ISBN: 978-0803937796
Alias	field theoretical sampling, in-situ theoretical sampling, fieldwork-driven theoretical sampling, grounded field sampling	maximum variation sampling, maximum diversity sampling, MVS, heterogeneous sampling	judgmental sampling, selective sampling, criterion-based sampling, purposeful sampling
Apparentées	3	5	4
Résumé	Field-based theoretical sampling is an iterative qualitative sampling strategy in which decisions about whom to observe or interview next are made during active fieldwork, guided by emerging theoretical insights from the data already collected. Rooted in Glaser and Strauss's grounded theory, it extends theoretical sampling into naturalistic, in-situ field settings — ethnographic sites, clinical environments, organizational contexts — where data collection and analysis proceed simultaneously.	Maximum variation sampling is a purposive qualitative sampling strategy in which the researcher deliberately selects cases that span the widest possible range of variation on dimensions central to the study. The goal is not statistical representation but the identification of common patterns that cut across diverse cases as well as the documentation of the unique ways each context shapes the phenomenon under investigation.	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.