Sammenlign metoder

	Sneboldsampling	Maximum Variation Sampling	Formålsbestemt udvælgelse
Fagområde	Surveymetodologi	Surveymetodologi	Surveymetodologi
Familie	Process / pipeline	Process / pipeline	Process / pipeline
Oprindelsesår	1961	1985 (Lincoln & Guba); elaborated 1990–2002 (Patton)	Formalized ~1980–1990
Ophavsperson	Leo A. Goodman	Lincoln & Guba; systematised by Michael Quinn Patton	Michael Quinn Patton (systematic articulation); roots in early qualitative inquiry
Type	Non-probability sampling technique	Purposive qualitative sampling strategy	Non-probability sampling strategy
Oprindelig kilde	Goodman, L. A. (1961). Snowball sampling. Annals of Mathematical Statistics, 32(1), 148–170.	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
Aliasser	chain-referral sampling, network sampling, respondent-driven sampling, referral sampling	maximum variation sampling, maximum diversity sampling, MVS, heterogeneous sampling	judgmental sampling, selective sampling, criterion-based sampling, purposeful sampling
Relaterede	3	5	4
Resumé	Snowball sampling is a non-probability recruitment technique in which initial participants (seeds) refer the researcher to others who meet the study criteria, and those referrals in turn refer further participants. The sample grows incrementally — like a rolling snowball — until the required size or theoretical saturation is reached. It is the method of choice when a target population has no accessible sampling frame, such as undocumented migrants, illicit drug users, survivors of stigmatised experiences, or members of closed professional networks.	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.