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Theory & Methods: Conditioning on Auxiliary Variable Means in Finite Population Inference
Author(s) -
Montanari Giorgio E.
Publication year - 2000
Publication title -
australian and new zealand journal of statistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.434
H-Index - 41
eISSN - 1467-842X
pISSN - 1369-1473
DOI - 10.1111/1467-842x.00138
Subject(s) - mathematics , estimator , conditional variance , statistic , conditional expectation , inference , statistics , conditional probability distribution , population , conditioning , econometrics , artificial intelligence , computer science , volatility (finance) , demography , sociology , autoregressive conditional heteroskedasticity
This paper reviews conditional properties of the mean and total estimators of a finite population when auxiliary information is available. An exact design‐based conditional analysis for complex sampling designs is intractable, but an asymptotic conditional framework can be developed. Within such a framework the paper establishes sufficient conditions for conditional unbiasedness and explores conditional properties of various types of regression estimators. A sample statistic capable of indicating the presence of substantial conditional biases is proposed, and illustrated by a simulation study.