Snowball sampling, also called network sampling or chain referral, is a non-probability sampling method where existing participants recruit future participants. This method is advantageous when the population of interest is hard to reach or not well-defined, and traditional sampling methods may be impractical.
Snowball sampling relies on social networks and connections to identify and recruit participants, creating a chain-like structure of referrals.
Advantages of snowball sampling include:
- Access to hard-to-reach populations: Snowball sampling effectively reaches populations that are hidden, marginalized, or difficult to access through traditional sampling methods.
- Cost-effective: It is cost-effective, especially when reaching out to individuals from diverse locations.
- Rapid recruitment: The method allows for relatively rapid recruitment, as participants are added to the sample in succession.
Some challenges while employing snowball sampling are:
- Sampling bias: Snowball sampling may introduce bias, as participants are recruited based on existing social networks and connections, potentially excluding those outside these networks.
- Limited representativeness: The sample may not represent the broader population, especially if some subgroups are overrepresented or underrepresented in the referral chain.
- Ethical concerns: There might be ethical concerns related to privacy, especially if participants are asked to disclose information about others without their consent.
- Difficulty in controlling sample composition: The researcher has limited control over the sample’s composition, as it depends on the choices made by participants in the referral process.
List of recommended resources #
For a broad overview #
This article by Laerd Dissertation explains what snowball sampling – a type of non-probability sampling – is, how to create a snowball sample and the various advantages and limitations of this sampling technique.
This blog on Scribbr by Kassiani Nikolopoulou gives an overview of snowball sampling, the different types of snowball sampling namely – linear snowball sampling, exponential non-discriminative snowball sampling, and exponential discriminative snowball sampling – as well as the advantages and disadvantages of this non-probability sampling method.
For in depth understanding #
This book by Michael Quinn Patton gives a comprehensive view of all the aspects of qualitative inquiry through new examples, stories, and cartoons. Part 2 of this book – Qualitative Designs and Data collection – in particular, focuses on different types of probability sampling methods and explains them with ease and clarity.
This article by Charlie Parker begins with a description of the conveniences of snowball sampling, followed by some criticisms and limitations of the technique. It also provides examples of how snowball sampling is used in qualitative research projects as well as examines instances in which snowball sampling stalls or fails to produce participants.
Case study #
This paper by Julian Kirchherr and Katrina Charles performs the first quantitative, medium-N analysis of snowball sampling to identify pathways to sample diversity for a research project on anti-dam movements in Southeast Asia.
This article by Kath Browne explores the use of snowball sampling particularly when the population under investigation is ‘hidden’ either due to low numbers of potential participants or the sensitivity of the topic, for example, research with women who do not fit within the hegemonic heterosexual norm.