{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T11:03:55Z","timestamp":1740135835281,"version":"3.37.3"},"reference-count":42,"publisher":"Wiley","issue":"3","license":[{"start":{"date-parts":[[2014,1,2]],"date-time":"2014-01-02T00:00:00Z","timestamp":1388620800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"funder":[{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"crossref","award":["T32 ES015459","R01 AI 97015"],"award-info":[{"award-number":["T32 ES015459","R01 AI 97015"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"crossref"}]},{"name":"Department for International Development of the UK","award":["40029926"],"award-info":[{"award-number":["40029926"]}]},{"name":"UNICEF","award":["43114258"],"award-info":[{"award-number":["43114258"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Tropical Med Int Health"],"published-print":{"date-parts":[[2014,3]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec><jats:title>Objectives<\/jats:title><jats:p>To assess the bias incurred when curtailment of Lot Quality Assurance Sampling (<jats:styled-content style=\"fixed-case\">LQAS<\/jats:styled-content>) 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.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>We present estimators of coverage when using two kinds of curtailed<jats:styled-content style=\"fixed-case\">LQAS<\/jats:styled-content>strategies: semicurtailed and curtailed. We study the proposed estimators with independent and clustered data using three field\u2010tested<jats:styled-content style=\"fixed-case\">LQAS<\/jats:styled-content>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.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>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<jats:styled-content style=\"fixed-case\">LQAS<\/jats:styled-content>design influences estimates of polio vaccination coverage in 20 Nigerian LGAs. When coverage is low, semicurtailed<jats:styled-content style=\"fixed-case\">LQAS<\/jats:styled-content>strategies considerably reduces the sample size required to make a decision. Curtailed<jats:styled-content style=\"fixed-case\">LQAS<\/jats:styled-content>designs further reduce the sample size when coverage is high.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusions<\/jats:title><jats:p>Results presented dispel the misconception that curtailed<jats:styled-content style=\"fixed-case\">LQAS<\/jats:styled-content>data are unsuitable for estimation. These findings augment the utility of<jats:styled-content style=\"fixed-case\">LQAS<\/jats:styled-content>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.<\/jats:p><\/jats:sec>","DOI":"10.1111\/tmi.12247","type":"journal-article","created":{"date-parts":[[2014,1,2]],"date-time":"2014-01-02T07:54:42Z","timestamp":1388649282000},"page":"321-330","source":"Crossref","is-referenced-by-count":4,"title":["Estimation after classification using lot quality assurance sampling: corrections for curtailed sampling with application to evaluating polio vaccination campaigns"],"prefix":"10.1111","volume":"19","author":[{"given":"Casey","family":"Olives","sequence":"first","affiliation":[{"name":"Department of Environmental and Occupational Health Sciences University of Washington Seattle WA USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Joseph J.","family":"Valadez","sequence":"additional","affiliation":[{"name":"Department of International Public Health Liverpool School of Tropical Medicine Liverpool UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Marcello","family":"Pagano","sequence":"additional","affiliation":[{"name":"Department of Biostatistics Harvard School of Public Health Boston MA USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2014,1,2]]},"reference":[{"key":"e_1_2_6_2_1","doi-asserted-by":"publisher","DOI":"10.2307\/2685469"},{"key":"e_1_2_6_3_1","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1111\/j.2517-6161.1953.tb00121.x","article-title":"Sequential estimation","volume":"15","author":"Anscombe F","year":"1953","journal-title":"Journal of the Royal Statistical Society. 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