Multiple category-lot quality assurance sampling: a new classification system with application to schistosomiasis control.
<h4>Background</h4>Originally a binary classifier, Lot Quality Assurance Sampling (LQAS) has proven to be a useful tool for classification of the prevalence of Schistosoma mansoni into multiple categories (≤10%, >10 and <50%, ≥50%), and semi-curtailed sampling has been shown to eff...
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| Language: | English |
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Public Library of Science (PLoS)
2012-01-01
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| Series: | PLoS Neglected Tropical Diseases |
| Online Access: | https://journals.plos.org/plosntds/article/file?id=10.1371/journal.pntd.0001806&type=printable |
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| author | Casey Olives Joseph J Valadez Simon J Brooker Marcello Pagano |
| author_facet | Casey Olives Joseph J Valadez Simon J Brooker Marcello Pagano |
| author_sort | Casey Olives |
| collection | DOAJ |
| description | <h4>Background</h4>Originally a binary classifier, Lot Quality Assurance Sampling (LQAS) has proven to be a useful tool for classification of the prevalence of Schistosoma mansoni into multiple categories (≤10%, >10 and <50%, ≥50%), and semi-curtailed sampling has been shown to effectively reduce the number of observations needed to reach a decision. To date the statistical underpinnings for Multiple Category-LQAS (MC-LQAS) have not received full treatment. We explore the analytical properties of MC-LQAS, and validate its use for the classification of S. mansoni prevalence in multiple settings in East Africa.<h4>Methodology</h4>We outline MC-LQAS design principles and formulae for operating characteristic curves. In addition, we derive the average sample number for MC-LQAS when utilizing semi-curtailed sampling and introduce curtailed sampling in this setting. We also assess the performance of MC-LQAS designs with maximum sample sizes of n=15 and n=25 via a weighted kappa-statistic using S. mansoni data collected in 388 schools from four studies in East Africa.<h4>Principle findings</h4>Overall performance of MC-LQAS classification was high (kappa-statistic of 0.87). In three of the studies, the kappa-statistic for a design with n=15 was greater than 0.75. In the fourth study, where these designs performed poorly (kappa-statistic less than 0.50), the majority of observations fell in regions where potential error is known to be high. Employment of semi-curtailed and curtailed sampling further reduced the sample size by as many as 0.5 and 3.5 observations per school, respectively, without increasing classification error.<h4>Conclusion/significance</h4>This work provides the needed analytics to understand the properties of MC-LQAS for assessing the prevalance of S. mansoni and shows that in most settings a sample size of 15 children provides a reliable classification of schools. |
| format | Article |
| id | doaj-art-33efe62bde8f469083ab72ee2f98edd7 |
| institution | OA Journals |
| issn | 1935-2727 1935-2735 |
| language | English |
| publishDate | 2012-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS Neglected Tropical Diseases |
| spelling | doaj-art-33efe62bde8f469083ab72ee2f98edd72025-08-20T02:22:45ZengPublic Library of Science (PLoS)PLoS Neglected Tropical Diseases1935-27271935-27352012-01-0169e180610.1371/journal.pntd.0001806Multiple category-lot quality assurance sampling: a new classification system with application to schistosomiasis control.Casey OlivesJoseph J ValadezSimon J BrookerMarcello Pagano<h4>Background</h4>Originally a binary classifier, Lot Quality Assurance Sampling (LQAS) has proven to be a useful tool for classification of the prevalence of Schistosoma mansoni into multiple categories (≤10%, >10 and <50%, ≥50%), and semi-curtailed sampling has been shown to effectively reduce the number of observations needed to reach a decision. To date the statistical underpinnings for Multiple Category-LQAS (MC-LQAS) have not received full treatment. We explore the analytical properties of MC-LQAS, and validate its use for the classification of S. mansoni prevalence in multiple settings in East Africa.<h4>Methodology</h4>We outline MC-LQAS design principles and formulae for operating characteristic curves. In addition, we derive the average sample number for MC-LQAS when utilizing semi-curtailed sampling and introduce curtailed sampling in this setting. We also assess the performance of MC-LQAS designs with maximum sample sizes of n=15 and n=25 via a weighted kappa-statistic using S. mansoni data collected in 388 schools from four studies in East Africa.<h4>Principle findings</h4>Overall performance of MC-LQAS classification was high (kappa-statistic of 0.87). In three of the studies, the kappa-statistic for a design with n=15 was greater than 0.75. In the fourth study, where these designs performed poorly (kappa-statistic less than 0.50), the majority of observations fell in regions where potential error is known to be high. Employment of semi-curtailed and curtailed sampling further reduced the sample size by as many as 0.5 and 3.5 observations per school, respectively, without increasing classification error.<h4>Conclusion/significance</h4>This work provides the needed analytics to understand the properties of MC-LQAS for assessing the prevalance of S. mansoni and shows that in most settings a sample size of 15 children provides a reliable classification of schools.https://journals.plos.org/plosntds/article/file?id=10.1371/journal.pntd.0001806&type=printable |
| spellingShingle | Casey Olives Joseph J Valadez Simon J Brooker Marcello Pagano Multiple category-lot quality assurance sampling: a new classification system with application to schistosomiasis control. PLoS Neglected Tropical Diseases |
| title | Multiple category-lot quality assurance sampling: a new classification system with application to schistosomiasis control. |
| title_full | Multiple category-lot quality assurance sampling: a new classification system with application to schistosomiasis control. |
| title_fullStr | Multiple category-lot quality assurance sampling: a new classification system with application to schistosomiasis control. |
| title_full_unstemmed | Multiple category-lot quality assurance sampling: a new classification system with application to schistosomiasis control. |
| title_short | Multiple category-lot quality assurance sampling: a new classification system with application to schistosomiasis control. |
| title_sort | multiple category lot quality assurance sampling a new classification system with application to schistosomiasis control |
| url | https://journals.plos.org/plosntds/article/file?id=10.1371/journal.pntd.0001806&type=printable |
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