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669 – Variance Estimation in Sample Surveys

Properties of Smoothed Design-Based Variance Estimators from Complex Sample Surveys

Sponsor: Section on Survey Research Methods
Keywords: Bias, Design-based inference, Model-based inference, Superpopulation model, U.S. Current Employment Statistics Program, Variance estimator stability

MoonJung Cho

Bureau of Labor Statistics

John Eltinge

Bureau of Labor Statistics

Julie Gershunskaya

Bureau of Labor Statistics

Larry Huff

Bureau of Labor Statistics

Due to relatively high levels of sampling variability, direct design-based variance estimators are often smoothed before publication. For example, some Federal Statistics programs publish the medians of a sequence of monthly direct variance estimates, or functions of these medians. The properties of these smoothed estimators depend on several underlying conditions, including sample size, effective degrees of freedom for the direct estimators; correlation of the direct estimators across months; and temporal patterns in the true variances. We compare and contrast these properties with the corresponding properties of generalized variance function (GVF) estimators.

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