Estimation after classification using lot quality assurance sampling: corrections for curtailed sampling with application to evaluating polio vaccination campaigns.

Olives, Casey, Valadez, Joseph ORCID: https://orcid.org/0000-0002-6575-6592 and Pagano, Marcello (2014) 'Estimation after classification using lot quality assurance sampling: corrections for curtailed sampling with application to evaluating polio vaccination campaigns.'. Tropical Medicine & International Health, Vol 19, Issue 3, pp. 321-330.

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Abstract

OBJECTIVES
To assess the bias incurred when curtailment of Lot Quality Assurance Sampling (LQAS) is ignored, to present unbiased estimators, to consider the impact of cluster sampling by simulation and to apply our method to published polio immunization data from Nigeria.

METHODS
We present estimators of coverage when using two kinds of curtailed LQAS strategies: semicurtailed and curtailed. We study the proposed estimators with independent and clustered data using three field-tested LQAS designs for assessing polio vaccination coverage, with samples of size 60 and decision rules of 9, 21 and 33, and compare them to biased maximum likelihood estimators. Lastly, we present estimates of polio vaccination coverage from previously published data in 20 local government authorities (LGAs) from five Nigerian states.

RESULTS
Simulations illustrate substantial bias if one ignores the curtailed sampling design. Proposed estimators show no bias. Clustering does not affect the bias of these estimators. Across simulations, standard errors show signs of inflation as clustering increases. Neither sampling strategy nor LQAS design influences estimates of polio vaccination coverage in 20 Nigerian LGAs. When coverage is low, semicurtailed LQAS strategies considerably reduces the sample size required to make a decision. Curtailed LQAS designs further reduce the sample size when coverage is high.

CONCLUSIONS
Results presented dispel the misconception that curtailed LQAS data are unsuitable for estimation. These findings augment the utility of LQAS as a tool for monitoring vaccination efforts by demonstrating that unbiased estimation using curtailed designs is not only possible but these designs also reduce the sample size.

Item Type:	Article
Subjects:	WA Public Health > Preventive Medicine > WA 115 Immunization WA Public Health > WA 20.5 Research (General) WC Communicable Diseases > WC 20 Research (General) WC Communicable Diseases > Virus Diseases > Viral Hemorrhagic Fevers. Other Virus Diseases > WC 556 Prevention and control
Faculty: Department:	Clinical Sciences & International Health > International Public Health Department
Digital Object Identifer (DOI):	https://doi.org/10.1111/tmi.12247
Depositing User:	Helen Fletcher
Date Deposited:	27 Mar 2014 12:47
Last Modified:	06 Sep 2019 11:29
URI:	https://archive.lstmed.ac.uk/id/eprint/3603

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