Non probability sampling

Non-Probability Sampling

Sampling is the use of a subset of the population to represent the whole population or to inform about (social) processes that are meaningful beyond the particular cases, individuals or sites studied.  Probability sampling, or random sampling, is a sampling technique in which the probability of getting any particular sample may be calculated.  Non probability sampling does not meet this criterion and, as any methodological decision, should adjust to the research question that one envisages to answer.  Non probability sampling techniques are not intended to be used to infer from the sample to the general population in statistical terms.  Instead, for example, grounded theory can be produced through iterative non-probability sampling until theoretical saturation is reached (Strauss and Corbin, 1990).

Thus, one cannot say the same on the basis of a non probability sample than on the basis of a probability sample. The grounds for drawing generalizations (e.g., propose new theory, propose policy) from studies based on non probability samples are based on the notion of "theoretical saturation" and "analytical generalization" (Yin, 2014) instead of on statistical generalization.  Researchers working with the notion of purposive sampling assert that while probability methods are suitable for large-scale studies concerned with representativeness, non-probability approaches are more suitable for in-depth qualitative research in which the focus is often to understand complex social phenomena (e.g., Marshall 1996; Small 2009)