Using Multi-Phase Sampling to Limit Respondent Burden Across Agriculture Surveys

Kott, Phillip S.; Fetter, Matthew J.

Using Multi-Phase Sampling to Limit Respondent Burden Across Agriculture Surveys

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Descripción

The National Agricultural Statistics Service is developing strategies that limit the amount of sample overlap across unrelated surveys by using multi-phase sampling principles. In its simplest form, Sample A is selected first, and then Sample B is chosen from among those members of the population not selected for Sample A. Effectively, Sample B is selected in two-phases. This two-phase approach extends easily to the coordination of more than two samples, although meeting accuracy and/or sample-size targets while maintaining strict sample exclusivity is not always possible. Variation of the basic approach address this problem, but lead to some theoretical difficulties. Sampling weights may be based on products of conditional selection probabilities rather than on unconditional selection probabilities. Randomization-based variance estimation likewise may depend on the product of conditional joint selection probabilities. In practice, variance estimates will be reasonable but may not always be randomization consistent.