Using successive difference replication for estimating variances

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Stephen Ash^{Note 1}

Abstract

Fay and Train (1995) present a method called successive difference replication that can be used to estimate the variance of an estimated total from a systematic random sample from an ordered list. The estimator uses the general form of a replication variance estimator, where the replicate factors are constructed such that the estimator mimics the successive difference estimator. This estimator is a modification of the estimator given by Wolter (1985). The paper furthers the methodology by explaining the impact of the row assignments on the variance estimator, showing how a reduced set of replicates leads to a reasonable estimator, and establishing conditions for successive difference replication to be equivalent to the successive difference estimator.

Key Words

Successive differences; Successive difference replication; Systematic random sampling

Table of content

• 1. Introduction
• 2. Successive difference replication
• 3. Empirical examples
• 4. Concluding remarks
• Acknowledgements
• Appendix
• References

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Notes

1. Stephen Ash, U.S. Census Bureau, 4600 Silver Hill Road, Washington DC 20233. E-mail: stephen.eliot.ash@census.gov.stephen.eliot.ash@census.gov.