Abstract
In order to obtain valid inference, the analysis of survey data requires special approaches to account
for sampling design features. This is particularly true for analyzing complex survey data
in which inclusion probabilities are not constant—as is the case, for example, in the National
Educational Panel Study (NEPS). One way to achieve proper results—even when a statistical
method does not explicitly account for survey design features—is the method of balanced repeated
replication. This methodology provides a correct assessment of the variances for a wide
range of estimators from stratified multistage sampling designs. Balanced repeated replication
can be applied without further ado if so-called replication weights are available. To facilitate an
unbiased variance estimation for NEPS data users, the NEPS methods group provides specific
replication weights for the students participating in the first wave of the NEPS fifth-grade sample
and for students participating in the first and the second wave of the NEPS ninth-grade sample
as well. Additionally, replication weights are provided for fifth and ninth graders, for whom an
interview with one parent could be realized. In this paper we describe how these weights have
been derived and how they can be used to yield valid variance estimates
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