Balanced Repeated Replication - DRAFT VERSION

Balanced repeated replication (BRR) is a method to estimate the sampling variability of a statistic that takes into account the properties of the sample design. It provides unbiased estimates of the sampling error arising from complex sample selection procedures. The estimates capture the effects of stratification, clustering, and unequal probabilities of selection. 

BRR works by repeatedly re-estimating the target statistics using half the sample at a time. When each sampling stratum contains two PSUs, replicates are formed by including one of the two PSUs from a stratum. If the sample includes H strata, such replicates can be formed.The variability of the target statistics across these replicates offers an estimate of the sampling variance of the estimates. 

Fay’s method is a variant of Balanced Repeated Replication in which less extreme adjustments are made to the weights for each replicate.For example, the “included” PSUs may have their weights increased by 50%, and the excluded PSUs would have their weights decreased by a corresponding amount.

Click on the Overview tab to read an overview of this statistical analysis. Click on the Details tab to learn more about the details of this analysis. Select the References tab to retrieve the references for this analysis. Select the In NAEP tab to see how this procedure applies in NAEP.