The problem of estimating the variance of the Horvitz-Thompson estimator under a probability proportional to size design is concerned. Some IPPS-bootstrap algorithms are proposed with the purpose of both simplifying available procedures and of improving efficiency. Results from a simulation study using both natural and artificial data are presented in order to empirically study the bias and stability of the bootstrap variance estimators proposed

Barbiero, A., Mecatti, F. (2009). Bootstrap algorithms for variance estimation in complex survey sampling. Intervento presentato a: S.CO2009 Complex Models and Computational Methods for Estimation and Prediction, Politecnico di Milano.

Bootstrap algorithms for variance estimation in complex survey sampling

MECATTI, FULVIA
2009

Abstract

The problem of estimating the variance of the Horvitz-Thompson estimator under a probability proportional to size design is concerned. Some IPPS-bootstrap algorithms are proposed with the purpose of both simplifying available procedures and of improving efficiency. Results from a simulation study using both natural and artificial data are presented in order to empirically study the bias and stability of the bootstrap variance estimators proposed
slide + paper
Horvitz-Thompson estimator, probability-proportional-to-size sampling, simulation
English
S.CO2009 Complex Models and Computational Methods for Estimation and Prediction
http://mox.polimi.it/sco2009/
Barbiero, A., Mecatti, F. (2009). Bootstrap algorithms for variance estimation in complex survey sampling. Intervento presentato a: S.CO2009 Complex Models and Computational Methods for Estimation and Prediction, Politecnico di Milano.
Barbiero, A; Mecatti, F
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/8768
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