<abstract xmlns="http://www.w3.org/1999/xhtml"><p>We investigate disproportionate stratified sampling as a possibly efficient method of surveying members of a rare domain in circumstances in which there is no acceptable list of members. In this work, we assume that information is available at the sampling stage to stratify the general-population sampling frame into high- and low-density strata. Under a fixed constraint on the variance of the estimator of the domain mean, we make the optimum allocation of sample size to the several strata and show that, in comparison to proportional allocation, the optimum allocation requires (a) a smaller total sample size but (b) a larger number of interviews of members of the rare domain. We illustrate the methods using information about American consumers maintained by market-research companies. Such companies are able to develop lists of households that are thought to have a defined attribute of interest, such as at least one resident in a user-specified age range. The lists are imperfect, with false positives and negatives. We apply an age-targeted list to the National Immunization Survey (NIS), conducted by the Centers for Disease Control and Prevention, which targets the relatively rare population of children age 19–35 months. The age-targeted list comprises the high-density stratum and the rest of the survey’s sampling frame comprises the low-density stratum. Given the optimum allocation, we demonstrate potential cost savings for the NIS in excess of ten percent.</p></abstract>

We investigate disproportionate stratified sampling as a possibly efficient method of surveying members of a rare domain in circumstances in which there is no acceptable list of members. In this work, we assume that information is available at the sampling stage to stratify the general-population sampling frame into high- and low-density strata. Under a fixed constraint on the variance of the estimator of the domain mean, we make the optimum allocation of sample size to the several strata and show that, in comparison to proportional allocation, the optimum allocation requires (a) a smaller total sample size but (b) a larger number of interviews of members of the rare domain. We illustrate the methods using information about American consumers maintained by market-research companies. Such companies are able to develop lists of households that are thought to have a defined attribute of interest, such as at least one resident in a user-specified age range. The lists are imperfect, with false positives and negatives. We apply an age-targeted list to the National Immunization Survey (NIS), conducted by the Centers for Disease Control and Prevention, which targets the relatively rare population of children age 19–35 months. The age-targeted list comprises the high-density stratum and the rest of the survey’s sampling frame comprises the low-density stratum. Given the optimum allocation, we demonstrate potential cost savings for the NIS in excess of ten percent.

Using Auxiliary Sample Frame Information for Optimum Sampling of Rare Populations

NORC – University of Chicago, 55 East Monroe Street Suite 3000, IL 60603-5805, Chicago, Illinois, U.S.A.

National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, 1600 Clifton Rd, Atlanta, GA 30333, U.S.A.

Journal of Official Statistics

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

We investigate disproportionate stratified sampling as a possibly efficient method of surveying members of a rare domain in circumstances in which there is no...

Using Auxiliary Sample Frame Information for Optimum Sampling of Rare Populations

Pubblicato online: 16 dic 2015

Pagine: 545 - 557

Ricevuto: 01 mag 2013

Accettato: 01 mar 2015

DOI: https://doi.org/10.1515/jos-2015-0034

Parole chiave
Optimum allocation, cost model, variance, disproportionate stratification, rare population, age-targeted list, telephone surveys, National Immunization Survey

© 2015 Martin Barron et al., published by De Gruyter Open

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Using Auxiliary Sample Frame Information for Optimum Sampling of Rare Populations

Pubblicato online: 16 dic 2015

Pagine: 545 - 557

Ricevuto: 01 mag 2013

Accettato: 01 mar 2015

DOI: https://doi.org/10.1515/jos-2015-0034

Parole chiaveOptimum allocation, cost model, variance, disproportionate stratification, rare population, age-targeted list, telephone surveys, National Immunization Survey

© 2015 Martin Barron et al., published by De Gruyter Open

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Parole chiave
Optimum allocation, cost model, variance, disproportionate stratification, rare population, age-targeted list, telephone surveys, National Immunization Survey