The Annals of Statistics

Endogenous post-stratification in surveys: Classifying with a sample-fitted model

F. Jay Breidt and Jean D. Opsomer

Full-text: Open access

Abstract

Post-stratification is frequently used to improve the precision of survey estimators when categorical auxiliary information is available from sources outside the survey. In natural resource surveys, such information is often obtained from remote sensing data, classified into categories and displayed as pixel-based maps. These maps may be constructed based on classification models fitted to the sample data. Post-stratification of the sample data based on categories derived from the sample data (“endogenous post-stratification”) violates the standard post-stratification assumptions that observations are classified without error into post-strata, and post-stratum population counts are known. Properties of the endogenous post-stratification estimator are derived for the case of a sample-fitted generalized linear model, from which the post-strata are constructed by dividing the range of the model predictions into predetermined intervals. Design consistency of the endogenous post-stratification estimator is established under mild conditions. Under a superpopulation model, consistency and asymptotic normality of the endogenous post-stratification estimator are established, showing that it has the same asymptotic variance as the traditional post-stratified estimator with fixed strata. Simulation experiments demonstrate that the practical effect of first fitting a model to the survey data before post-stratifying is small, even for relatively small sample sizes.

Article information

Source
Ann. Statist., Volume 36, Number 1 (2008), 403-427.

Dates
First available in Project Euclid: 1 February 2008

Permanent link to this document
https://projecteuclid.org/euclid.aos/1201877307

Digital Object Identifier
doi:10.1214/009053607000000703

Mathematical Reviews number (MathSciNet)
MR2387977

Zentralblatt MATH identifier
1132.62006

Subjects
Primary: 62D05: Sampling theory, sample surveys
Secondary: 62F12: Asymptotic properties of estimators

Keywords
Calibration classification design consistency generalized linear model Horvitz–Thompson estimator ratio estimator stratification survey regression estimator

Citation

Breidt, F. Jay; Opsomer, Jean D. Endogenous post-stratification in surveys: Classifying with a sample-fitted model. Ann. Statist. 36 (2008), no. 1, 403--427. doi:10.1214/009053607000000703. https://projecteuclid.org/euclid.aos/1201877307


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