Disproportional cluster sampling
Disproportional cluster sampling is a probability-based survey design in which naturally occurring groups (clusters) are selected as primary sampling units, but the number of clusters or elements drawn from each group is not proportional to that group's share of the population. By deliberately over- or under-sampling certain clusters, researchers gain analytic flexibility and precision where it matters most, at the cost of requiring post-hoc weighting for population-level inference.
Source record
Citations copied verbatim from the method’s source record. No claim-level verification is inferred from them.
- Kish, L. (1965). Survey Sampling. John Wiley & Sons. · ISBN 978-0471489009
- Cochran, W. G. (1977). Sampling Techniques (3rd ed.). John Wiley & Sons. · ISBN 978-0471162407
Curated claims
Claims persisted in the evidence ledger, each with its own assessment.
This view does not invent a claim assessment when the ledger has none.
Related methods
Generated from the method graph and shown as machine-suggested relations — no evidence claim is inferred.