Editing Nonprobability sampling (section)

== 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>