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In sociology and statistics research, snowball sampling [1] (or chain sampling, chain-referral sampling, referral sampling [2] [3]) is a nonprobability sampling technique where existing study subjects recruit future subjects from among their acquaintances. Thus the sample group is said to grow like a rolling snowball.
Consecutive sampling, also known as total enumerative sampling, [7] is a sampling technique in which every subject meeting the criteria of inclusion is selected until the required sample size is achieved. [8] [9] Snowball sampling, involving the first respondent referring an
In social science research, snowball sampling is a similar technique, where existing study subjects are used to recruit more subjects into the sample. Some variants of snowball sampling, such as respondent driven sampling, allow calculation of selection probabilities and are probability sampling methods under certain conditions.
This category is for techniques for statistical sampling from real-world populations, used in observational studies and surveys. For techniques for sampling random numbers from desired probability distributions, see category:Monte Carlo methods.
In social science research, snowball sampling, or "snowballing": a technique for developing a research sample; In researching a field, snowballing is another name for Pearl growing; In chemical and industrial engineering, snowballing is the second and last phase, after aggregation, of the pelletization process.
Sampling methods may be either random (random sampling, systematic sampling, stratified sampling, cluster sampling) or non-random/nonprobability (convenience sampling, purposive sampling, snowball sampling). [3] The most common reason for sampling is to obtain information about a population.
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Snowball sampling; Sobel test; Social network change detection; Social statistics; SOFA Statistics – software; Soliton distribution – redirects to Luby transform code; Somers' D; Sørensen similarity index; Spaghetti plot; Sparse binary polynomial hashing; Sparse PCA – sparse principal components analysis; Sparsity-of-effects principle ...