Abstract #300094

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JSM 2003 Abstract #300094
Activity Number: 76
Type: Topic Contributed
Date/Time: Monday, August 4, 2003 : 8:30 AM to 10:20 AM
Sponsor: Section on Survey Research Methods
Abstract - #300094
Title: Variance Estimation and Inference for Stratified Sample Designs with Nontrivial Sample Fractions and Nonresponse
Author(s): John L. Eltinge*+
Companies: Bureau of Labor Statistics
Address: 3316 Saddlestone Ct., Oakton, VA, 22124-1910,
Keywords: Balanced repeated replication with Fay factors ; Influence function ; Quasirandomization model ; Sparse-effect model ; Stratum collapse ; Variance estimator stability
Abstract:

In establishment surveys, sample designs often include stratification by the size of the establishment, with large establishments included in strata that have nontrivial sample fractions. For these designs, development and evaluation of appropriate variance estimators generally involve trade-offs among several factors, including the following: (1) the intended use of the variance estimator, e.g., for formal inference or for construction of weights in a weighted-least-squares procedure; (2) the extent, if any, to which one must account for nonresponse effects; (3) the relative magnitudes of the effects of standard variance approximation methods, e.g., stratum collapse. (4) the simplicity and ease of implementation within a given agency production environment.

This paper explores issues (1)-(4), with principal emphasis on diagnostics to identify acute problems with variance estimator bias or instability. The paper also adapts sparse-effect models from the experimental design literature to evaluate some properties of the proposed diagnostics.

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