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Sampling with Field Burden Constraints: An Application to Sheltered Homeless and Low-Income Housed Women

RAND

Daniela Golinelli

RAND

Katrin Hambarsoomian

RAND

Judith Perlman

RAND

Suzanne L. Wenzel

RAND

In this article, the authors present a statistically efficient, cost-effective way of collecting a probability sample in the presence of certain field burden constraints: restrictions on the maximum number of participants that can be sampled within a given institution and a small population size relative to the sample size dictated by the study aims. The authors suggest the use of disproportionate stratified random sampling as an alternative to two-stage sampling under these circumstances and illustrate how to account, via weighting, for the participants’ differential probabilities of inclusion. They describe their approach with respect to a study of impoverished women, for which this sampling scheme was quite effective.

Key Words: cluster sampling • stratified sampling • cost-effectiveness • weighting • vulnerable populations

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