Salīdzināt metodes

	Mērķtiecīgā izlase	Kvotu izlase	Sniegpulksteņa (vai ķēdes) izlase
Nozare	Aptauju metodoloģija	Aptauju metodoloģija	Aptauju metodoloģija
Saime	Process / pipeline	Process / pipeline	Process / pipeline
Izcelsmes gads	Formalized ~1980–1990	1930s	1961
Autors	Michael Quinn Patton (systematic articulation); roots in early qualitative inquiry	Developed in market research and opinion polling, notably applied by George Gallup in the 1930s	Leo A. Goodman
Tips	Non-probability sampling strategy	Non-probability sampling design	Non-probability sampling technique
Pirmavots	Patton, M. Q. (1990). Qualitative Evaluation and Research Methods (2nd ed.). Sage. ISBN: 978-0803937796	Moser, C. A., & Kalton, G. (1972). Survey Methods in Social Investigation (2nd ed.). Heinemann. ISBN: 978-0435827496	Goodman, L. A. (1961). Snowball sampling. Annals of Mathematical Statistics, 32(1), 148–170.
Citi nosaukumi	judgmental sampling, selective sampling, criterion-based sampling, purposeful sampling	quota-controlled sampling, quota selection, non-probability quota sampling	chain-referral sampling, network sampling, respondent-driven sampling, referral sampling
Saistītās	4	5	3
Kopsavilkums	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.	Quota sampling is a non-probability technique in which the researcher pre-specifies how many units to recruit from each subgroup (quota cell) defined by one or more control variables such as age, gender, or occupation. Interviewers or data collectors then use their own judgment to find and enroll participants until each cell is filled. The method guarantees the sample mirrors the population on the control variables but does not provide the randomness needed for classical statistical inference.	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.