A COMPARISON OF DESIGN‐BASED AND MODEL‐BASED ESTIMATORS OF THE FINITE POPULATION DISTRIBUTION FUNCTION
作者:
Alan H. Dorfman,
期刊:
Australian Journal of Statistics
(WILEY Available online 1993)
卷期:
Volume 35,
issue 1
页码: 29-41
ISSN:0004-9581
年代: 1993
DOI:10.1111/j.1467-842X.1993.tb01310.x
出版商: Blackwell Publishing Ltd
关键词: Auxiliary information;model fitting;regression diagnostics;sample survey
数据来源: WILEY
摘要:
SummaryRival estimators of the distribution function of a finite population, derived from the model‐based and design‐based approaches to sampling inference, are compared. A design‐based estimator due to Rao, Kovar&Mantel (1990) has the desirable property from a model‐based viewpoint, of being model‐unbiased under misspecification of model, when the sample meets certain conditions. A modified version of this estimator is suggested; it relies less on design‐based ingredients, and in particular avoids second‐order inclusion probabilities. It is the preferred estimator when, as is often the case in sampling practice, the model is adopted without thorough consideration of goodness of fit. However, if standard regression procedures of model construction and criticism are employed, then a strictly model‐based estima
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