Chinese Quarterly Journal of Mathematics ›› 2006, Vol. 21 ›› Issue (2): 309-316.

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A Model-calibration Approach to Using Complete Auxiliary Information from Stratified Sampling Survey Data

  

  1. School of Mathematics and Information Sciences, Jiaxing University, Jiaxing 314001, China;LPMC and School of Mathematical Sciences, Nankai University, Tianjin 300071, China
  • Received:2004-03-10 Online:2006-06-30 Published:2023-12-13
  • About author:WU Chang-chun(1966-),male,native of Qidong,Hunan,a professor of Jiaxing University, engages in mathematical statistics.
  • Supported by:
     Supported by the National Natural Science Foundation of China(10571093);

Abstract: In stratified survey sampling, sometimes we have complete auxiliary information. One of the fundamental questions is how to effectively use the complete auxiliary information at the estimation stage. In this paper, we extend the model-calibration method to obtain estimators of the finite population mean by using complete auxiliary information from stratified sampling survey data. We show that the resulting estimators effectively use auxiliary information at the estimation stage and possess a number of attractive features such as asymptotically design-unbiased irrespective of the working model and approximately model-unbiased under the model. When a linear working-model is used, the resulting estimators reduce to the usual calibration estimator(or GREG). 

Key words:  , model-calibration, pseudo empirical likelihood, stratified sampling survey, com- plete auxiliary information, estimating equations, generalized linear models, superpopulation ,  

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