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A Note on Robust Variance Estimation for Cluster‐Correlated Data
Author(s) -
Williams Rick L.
Publication year - 2000
Publication title -
biometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.298
H-Index - 130
eISSN - 1541-0420
pISSN - 0006-341X
DOI - 10.1111/j.0006-341x.2000.00645.x
Subject(s) - estimator , minimum variance unbiased estimator , variance (accounting) , cluster sampling , statistics , bias of an estimator , cluster (spacecraft) , computer science , consistent estimator , range (aeronautics) , robust statistics , survey sampling , sampling (signal processing) , mathematics , econometrics , medicine , population , materials science , accounting , environmental health , filter (signal processing) , business , composite material , computer vision , programming language
Summary. There is a simple robust variance estimator for cluster‐correlated data. While this estimator is well known, it is poorly documented, and its wide range of applicability is often not understood. The estimator is widely used in sample survey research, but the results in the sample survey literature are not easily applied because of complications due to unequal probability sampling. This brief note presents a general proof that the estimator is unbiased for cluster‐correlated data regardless of the setting. The result is not new, but a simple and general reference is not readily available. The use of the method will benefit from a general explanation of its wide applicability.