Combining data from two independent surveys: a model-assisted approach

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Combining information from two or more independent surveys is a problem frequently encountered in survey sampling. We consider the case of two independent surveys, where a large sample from survey 1 collects only auxiliary information and a much smaller sample from survey 2 provides information on both the variables of interest and the auxiliary variables. We propose a model-assisted projection method of estimation based on a working model, but the reference distribution is design-based. We generate synthetic or proxy values of a variable of interest by first fitting the working model, relating the variable of interest to the auxiliary variables, to the data from survey 2 and then predicting the variable of interest associated with the auxiliary variables observed in survey 1. The projection estimator of a total is simply obtained from the survey 1 weights and associated synthetic values. We identify the conditions for the projection estimator to be asymptotically unbiased. Domain estimation using the projection method is also considered. Replication variance estimators are obtained by augmenting the synthetic data file for survey 1 with additional synthetic columns associated with the columns of replicate weights. Results from a simulation study are presented
Publisher
OXFORD UNIV PRESS
Issue Date
2012-03
Language
English
Article Type
Article
Keywords

MULTIPLE SURVEYS; INFORMATION; REGRESSION; ESTIMATORS; IMPUTATION; SUPERPOPULATION; ERROR

Citation

BIOMETRIKA, v.99, no.1, pp.85 - 100

ISSN
0006-3444
DOI
10.1093/biomet/asr063
URI
http://hdl.handle.net/10203/212937
Appears in Collection
MA-Journal Papers(저널논문)
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