השוואת שיטות

	דגימת מקרים חריגים פיילוטית	דגימת מקרה חריג	דגימת מטרה (Purposive Sampling)
תחום	מתודולוגיית סקרים	מתודולוגיית סקרים	מתודולוגיית סקרים
משפחה	Process / pipeline	Process / pipeline	Process / pipeline
שנת המקור	2002 (Patton codification); pilot study tradition mid-20th century	1990	Formalized ~1980–1990
הוגה השיטה	Patton (deviant case sampling); pilot study methodology attributed broadly to pre-main-study practice traditions	Michael Quinn Patton	Michael Quinn Patton (systematic articulation); roots in early qualitative inquiry
סוג	Purposive sampling variant applied in pilot phase	Purposive qualitative sampling strategy	Non-probability sampling strategy
מקור מכונן	Patton, M. Q. (2002). Qualitative Research and Evaluation Methods (3rd ed.). Sage. [Chapter 5: Sampling Strategies, pp. 230–246 on deviant/extreme case sampling] ISBN: 978-0761919711	Patton, M. Q. (2002). Qualitative Research and Evaluation Methods (3rd ed.). Sage Publications. ISBN: 978-0761919711	Patton, M. Q. (1990). Qualitative Evaluation and Research Methods (2nd ed.). Sage. ISBN: 978-0803937796
כינויים	pilot extreme case sampling, pilot outlier sampling, pilot atypical case sampling, pilot deviant-case pilot sampling	extreme case sampling, outlier sampling, negative case sampling, deviant-case selection	judgmental sampling, selective sampling, criterion-based sampling, purposeful sampling
קשורות	2	5	4
תקציר	Pilot deviant case sampling is a purposive sampling strategy applied during a pilot phase in which participants are deliberately selected because they represent extreme, unusual, or atypical instances of the phenomenon under study. Rather than seeking representative participants for the pilot run, the researcher intentionally recruits outlier cases to probe the boundaries of research instruments, interview guides, or data collection protocols before the main study begins.	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.	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.