What is a potential downside of snowball sampling?

The selection of snowball sampling can indeed introduce bias into the sample. This method relies on existing subjects to recruit future subjects from their acquaintances. While this approach is useful for reaching populations that are hard to access, it can lead to a sample that is not representative of the broader population.

The connections between individuals can result in clusters of similar characteristics, leading to a lack of diversity in the sample. For example, if one participant refers only friends from a close-knit community, the resulting sample might share similar socioeconomic backgrounds, experiences, or opinions, which can skew the research results. This bias impacts the generalizability of the findings, as the specific traits of the participants may not reflect those of the entire population being studied.

While complexity, time consumption, and questions of scientific validity are considerations in research methods, they do not directly address the fundamental concern of representativeness and bias that comes with snowball sampling. By focusing on the potential for bias, one can recognize the importance of designing sampling methods that yield a more inclusive and valid representation of the population.