When little is known about a phenomenon or setting, a priori sampling decisions can be difficult. Qualitative researchers typically make sampling choices that enable them to achieve a deep understanding of the phenomenon they are studying. This was the case for Steven Kogan and colleagues (Kogan, Wejnert, Chen, Brody, & Slater, 2011)  who wished to study the sexual behaviors of non-college-bound African American young adults who lived in high-poverty rural areas. A researcher begins with specific characteristics in mind that they wish to examine and then they seek out research participants who cover that full range of characteristics. In addition, it is possible that your review of literature on the topic suggests that campus housing experiences vary by gender. 1.1 How do social workers know what to do? When are nonprobability samples ideal? Nonprobability sampling refers to sampling techniques for which a person’s likelihood of being selected for membership in the sample is unknown. For example, a researcher interested in studying how people with genital herpes cope with their medical condition would be unlikely to find many participants by posting an ad in the newspaper or by announcing the study at a social gathering. Convenience Sampling: This is a sampling technique that qualitative researchers use to recruit participants who are easily accessible and convenient to the researchers. Later, we’ll look more closely at the process of selecting research elements when drawing a nonprobability sample. When the researcher desires to choose members selectively,non-probability sampling is considered. There are several types of nonprobability samples that researchers use. 12.2 Pre-experimental and quasi-experimental design. (2011). There are additional sampling techniques, such as snowball and quota sampling, that qualitative researchers can use, but the majority of qualitative researchers utilize one of the sampling techniques described above. From these examples, we can see that nonprobability samples are useful for setting up, framing, or beginning any type of research, but it isn’t just early stage research that relies on and benefits from nonprobability sampling techniques. This one sentence description alone can already generate two selection criteria: (a) must be an active nurse and (b) must work at a specific hospital setting. Another example would be a professional who is a member of a professional organization and wanted to recruit participants through contact information available to members of that organization. That said, this does not mean that nonprobability samples are drawn arbitrarily or without any specific purpose in mind (that would mean committing one of the errors of informal inquiry discussed in Chapter 1). http://www.pbs.org/fmc/timeline/e1948election.htm. The researchers initially relied on their own networks to identify study participants, but members of the study’s target population were not easy to find. The Literary Digest, the leading polling entity at the time, predicted that Alfred Landon would beat Franklin Roosevelt in the presidential election by a landslide, but Gallup’s polling disagreed. Sampling is one of the most important aspects of research design. Since we don’t know the likelihood of selection, we don’t know whether a nonprobability sample is truly representative of a larger population. Thus, the researcher’s sample builds and becomes larger as the study continues, much as a snowball builds and becomes larger as it rolls through the snow. Sampling techniques can be used in conjunction with one another very easily or can be used alone within a qualitative dissertation. 13.3 Issues to consider for all interview types. Scientific Inquiry in Social Work by Matthew DeCarlo is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License, except where otherwise noted. In this nonprobability sampling method, subgroups are created based on each category, the researcher decides how many people to include from each subgroup, and then collects data from that number for each subgroup. Boston, MA: Pearson. First, you need to understand the difference between a population and a sample, and identify the target population of your research. The two most popular sampling techniques are purposeful and convenience sampling because they align the best across nearly all qualitative research designs. Participants were given an added incentive for referring eligible study participants; they received $50 for participating in the study and an additional $20 for each person they recruited who also participated in the study. In this case, a purposive sample might gather clinicians, current patients, administrators, staff, and former patients so they can talk as a group. Let’s consider a study of student satisfaction with on-campus housing. This article considers and explains the differences between the two approaches and describes three broad categories of naturalistic sampling: convenience, judgement and theoretical models.