Variance approximation under balanced sampling
Author(s)
Deville, Jean-Claude
Date issued
2005
In
Journal of Statistical Planning and Inference, Elsevier
Vol
128
No
2
From page
569
To page
591
Subjects
Sampling design Balanced sampling Unequal probability sampling Variance approximation Variance estimation Sampling theory Sample surveys Sample Sampling unequal probability
Abstract
A balanced sampling design has the interesting property that Horvitz–Thompson estimators of totals for a set of balancing variables are equal to the totals we want to estimate, therefore the variance of Horvitz–Thompson estimators of variables of interest are reduced in function of their correlations with the balancing variables. Since it is hard to derive an analytic expression for the joint inclusion probabilities, we derive a general approximation of variance based on a residual technique. This approximation is useful even in the particular case of unequal probability sampling with fixed sample size. Finally, a set of numerical studies with an original methodology allows to validate this approximation.
Publication type
journal article
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