Editing Nonprobability sampling

{{Short description|Sampling method}}
'''Nonprobability sampling''' is a form of [[Sampling (statistics)|sampling]] that does not utilise random sampling techniques where the probability of getting any particular sample may be calculated. 

Nonprobability samples are not intended to be used to infer from the sample to the general population in statistical terms. In cases where external validity is not of critical importance to the study's goals or purpose, researchers might prefer to use nonprobability sampling. Researchers may seek to use iterative nonprobability sampling for theoretical purposes, where analytical generalization is considered over statistical generalization.<ref>(Strauss and Corbin, 1990)</ref><ref>(Yin, 2014)</ref>

== Advantages and disadvantages ==
While probabilistic methods are suitable for large-scale studies concerned with representativeness, nonprobability approaches may be more suitable for in-depth qualitative research in which the focus is often to understand complex social phenomena.<ref>(Marshall 1996; Small 2009)</ref> The in-depth analysis of a small purposive sample or case study enables the discovery and identification of patterns and causal mechanisms that do not draw time and context-free assumptions. Another advantage of nonprobability sampling is its lower cost compared to probability sampling. 

Nonprobability sampling is often not appropriate in statistical quantitative research.<ref>(Lucas 2014a)</ref>

== Examples ==
Nonprobability sampling is widely used in qualitative research. Examples of nonprobability sampling include:
* [[Convenience sampling]], where members of the population are chosen based on their relative ease of access. Such samples are biased because researchers may unconsciously approach some kinds of respondents and avoid others,<ref>(Lucas 2014a)</ref> and respondents who volunteer for a study may differ in important ways from others.<ref>(Wiederman 1999)</ref>
* [[Consecutive sampling]], also known as total enumerative sampling,<ref name="Suresh2014">{{cite book|last1=Suresh|first1=Sharma|title=Nursing Research and Statistics|date=2014|publisher=Elsevier Health Sciences|isbn=9788131237861|page=224|url=https://books.google.com/books?id=9RyMBgAAQBAJ&q=%22consecutive+sampling%22&pg=PA224|access-date=29 September 2017|language=en}}</ref> is a sampling technique in which every subject meeting the criteria of inclusion is selected until the required sample size is achieved.<ref name="Schuster2005">{{cite book|last1=Schuster|first1=Daniel P.|last2=Powers (MD.)|first2=William J.|title=Translational and Experimental Clinical Research|date=2005|publisher=Lippincott Williams & Wilkins|isbn=9780781755658|page=46|url=https://books.google.com/books?id=C7pZftbI0ZMC&q=%22consecutive+sampling%22&pg=PA46|access-date=29 September 2017|language=en}}</ref><ref name="Bowers2011">{{cite book|last1=Bowers|first1=David|last2=House|first2=Allan|last3=Owens|first3=David H.|title=Getting Started in Health Research|date=2011|publisher=John Wiley & Sons|isbn=9781118292969|url=https://books.google.com/books?id=t729l9LE9NUC&q=Consecutive+sampling&pg=PT46|access-date=29 September 2017|language=en}}</ref> 
* [[Snowball sampling]], involving the first respondent referring an acquaintance, and so on. Such samples are biased because they give people with more social connections an unknown but higher chance of selection,<ref>(Berg 2006)</ref> but lead to higher response rates.
* [[Judgment sample|Judgment sampling]] or purposive sampling, where the researcher chooses the sample based on who they think would be appropriate for the study.<ref>{{Cite journal |last=Ahmed |first=Sirwan Khalid |date=December 2024 |title=How to choose a sampling technique and determine sample size for research: A simplified guide for researchers |url=https://linkinghub.elsevier.com/retrieve/pii/S2772906024005089 |journal=Oral Oncology Reports |language=en |volume=12 |pages=100662 |doi=10.1016/j.oor.2024.100662}}</ref> This is used primarily when there is a limited number of people that have expertise in the area being researched, or when the interest of the research is on a specific field or a small group. Types of purposive sampling include:
** Deviant case: The researcher obtains cases that substantially differ from the dominant pattern. The case is selected in order to obtain information on unusual cases that can be specially problematic or specially good.
** Case study: The research is limited to one group, often with a similar characteristic or of small size.

* [[Quota sampling]]. This is similar to [[Stratified sampling|stratified random sampling]], in which the researcher identifies subsets of the population of interest and then sets a target number for each category in the sample. Next, the researcher samples from the population of interest nonrandomly until the quotas are filled.<ref>(Steinke, 2004)</ref>

Studies intended to use probability sampling sometimes unintentionally end up using nonprobability samples because of characteristics of the sampling method. The statistical model used can also render the data a nonprobability sample.<ref>(Lucas, 2014b)</ref>

==See also==
* [[Sampling (statistics)]]
* [[Cluster sampling]]
* [[Multistage sampling]]
* [[Simple random sample]]
* [[Systematic sampling]]

==References==
{{Reflist|30em}}
*Berg, Sven.  (2006).  "Snowball Sampling–I," pp.&nbsp;7817–7821 in ''Encyclopedia of Statistical Sciences'', edited by Samuel Kotz, Campbell Read, N. Balakrishnan, and Brani Vidakovic.  Hoboken, NJ: John Wiley and Sons, Inc.
*Lucas, Samuel R. (2014a).  [https://doi.org/10.1007%2Fs11135-012-9775-3 "Beyond the Existence Proof:  Ontological Conditions, Epistemological Implications, and In-Depth Interview Research."],  ''Quality & Quantity'', 48: 387–408. {{doi|10.1007/s11135-012-9775-3}}.
*Lucas, Samuel R. (2014b).  [https://link.springer.com/content/pdf/10.1007%2Fs11135-013-9865-x.pdf "An Inconvenient Dataset: Bias and Inappropriate Inference in the Multilevel Model."],  ''Quality & Quantity'', 48: 1619–1649. {{doi|10.1007/s11135-013-9865-x}}
*Marshall, Martin N. (1996). "Sampling for Qualitative Research." ''Family Practice'' 13: 522–526. {{doi|10.1093/fampra/13.6.522}}
*Small, Mario L. (2009). "‘How many cases do I need?’ On science and the logic of case selection in field-based research." ''Ethnography'' 10: 5–38. {{doi|10.1177/1466138108099586}}
*Steinke, I. (2004). "Quality criteria in qualitative research". ''A companion to qualitative research'', 184–190. London: Sage Publications
*Strauss, A. and Corbin, J. (1990). [http://www.li.suu.edu/library/circulation/Stein/Comm%206020ksStraussCorbinBasicsQualitativeFall07.pdf "Basics of Qualitative Research"]. London: Sage Publications.
* Wiederman, Michael W.  (1999).  "Volunteer bias in sexuality research using college student participants." ''Journal of Sex Research'', 36: 59–66, {{doi|10.1080/00224499909551968}}.
*Yin, Robert K. (2014[1984]). ''Case study research: Design and methods''. Thousand Oaks: Sage publications.

{{DEFAULTSORT:Nonprobability Sampling}}
[[Category:Sampling techniques]]