Using successive difference replication for estimating variances - ARCHIVED

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.