Researcher chooses people or things that demonstrate a growing theory, to uncover variations of the theories among various sub-groups
Extreme or deviant case sampling
Researcher chooses samples of individuals or groups that represent extreme instances of the phenomenon being studied
Intensity sampling
Chooses participants that exhibit the phenomenon strongly but not excessively, provides rich information
Heterogenous/maximum variation sampling
Researcher chooses a diverse group of people or units that are impacted by the topic of interest, to gather information that outlines and clarifies the main ideas and trends
Homogenous sampling
Only samples that share specific predefined features are chosen, advantage of assisting in the reduction of variances and simplifying the analysis procedure
Snowball or chain sampling
When it is difficult to locate the individuals of the target population, one or two respondents will assist the researcher in locating other respondents
Critical case sampling
Researcher chooses samples that include crucial data, to understand each population's situation and draw generalizations to other populations
Criterion sampling
Researcher establishes a list of requirements before choosing samples that satisfy those requirements
Opportunistic or emergent sampling
Researcher starts to notice any new or unexpected themes and looks for fresh sources of information to contribute to the analysis
Typical case sampling
Researcher collects data from typical respondents as opposed to exceptional ones
Stratifiedpurposefulsampling
Target population is divided into several groups based on a variety of criteria, and a sample from each group is carefully chosen
Purposeful random sampling
Researcher will pick a small sample from a bigger set of populations that are relevant to the study, participants are chosen at random
Combination or mixed purposeful sampling
Researcher combines two or more of the aforementioned sample strategies