A new sampling design is derived for sampling a rare and clustered population under both cost and logistic constraints. It is motivated based on the example of national TB prevalence surveys, sponsored by WHO for high TB-burden countries and usually located in the poorest parts of the world. A Poisson-type sampling design named Poisson Sequential Adaptive (PoSA) is proposed with a twofold purpose: (i) to increase the detection rate of positive cases; and (ii) to reduce survey costs by accounting for logistic constraints at the design level of the survey. PoSA is derived by integrating both an adaptive component able to enhace detectability and a sequential component for dealing with costs and logistic constraints. An unbiased HT-type estimator for the population prevalence (mean) is derived by adjusting for both the over-selection bias and for the conditional structure induced by the sequential selection. Unbiased variance estimation in a closed form is also provided. Simulation results are presented and show a significant pontential of PoSA in improving the sampling methodology currently suggested by WHO guidelines.

Furfaro, E., Mecatti, F., New Perspectives In Sampling Rare and Clustered Populations, in 2016 JSM Proceedings - Survey Research Methods Section, (Chicago (USA), 30-July 02-August 2016), American Statistical Association (ASA), Chicago 2016: 2457-2466 [http://hdl.handle.net/10807/100608]

New Perspectives In Sampling Rare and Clustered Populations

Furfaro, Emanuela
Primo
;
2016

Abstract

A new sampling design is derived for sampling a rare and clustered population under both cost and logistic constraints. It is motivated based on the example of national TB prevalence surveys, sponsored by WHO for high TB-burden countries and usually located in the poorest parts of the world. A Poisson-type sampling design named Poisson Sequential Adaptive (PoSA) is proposed with a twofold purpose: (i) to increase the detection rate of positive cases; and (ii) to reduce survey costs by accounting for logistic constraints at the design level of the survey. PoSA is derived by integrating both an adaptive component able to enhace detectability and a sequential component for dealing with costs and logistic constraints. An unbiased HT-type estimator for the population prevalence (mean) is derived by adjusting for both the over-selection bias and for the conditional structure induced by the sequential selection. Unbiased variance estimation in a closed form is also provided. Simulation results are presented and show a significant pontential of PoSA in improving the sampling methodology currently suggested by WHO guidelines.
Inglese
2016 JSM Proceedings - Survey Research Methods Section
2017 Joint Statistical Meetings
Chicago (USA)
30-lug-2016
2-ago-2016
978-0-9839375-6-2
American Statistical Association (ASA)
Furfaro, E., Mecatti, F., New Perspectives In Sampling Rare and Clustered Populations, in 2016 JSM Proceedings - Survey Research Methods Section, (Chicago (USA), 30-July 02-August 2016), American Statistical Association (ASA), Chicago 2016: 2457-2466 [http://hdl.handle.net/10807/100608]
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/10807/100608
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