{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,16]],"date-time":"2026-10-16T02:41:22Z","timestamp":1792118482692,"version":"4.4.0"},"reference-count":23,"publisher":"SAGE Publications","issue":"4","license":[{"start":{"date-parts":[[2018,6,12]],"date-time":"2018-06-12T00:00:00Z","timestamp":1528761600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["JDR Clinical &amp; Translational Research"],"published-print":{"date-parts":[[2018,10]]},"abstract":"<jats:sec>\n                    <jats:title>Aim:<\/jats:title>\n                    <jats:p>The effect of misclassification of a cluster-level dichotomous outcome (disease) due to partial-cluster sampling on its association with a dichotomous exposure is investigated.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods:<\/jats:title>\n                    <jats:p>Disease (e.g., chronic periodontitis) is deemed to exist in a cluster (e.g., full mouth) when a condition of interest (e.g., pocket depth or clinical attachment loss exceeding an established threshold) is present in number and pattern across observations (e.g., tooth sites) in the cluster according to a specific criterion. When a subset of observations within each cluster is selected (i.e., partial-mouth sampling), specificity of disease is 100% (in the absence of site-level measurement error), whereas sensitivity is imperfect and generally unknown. Using conditional probability arguments, we investigate disease misclassification under partial-cluster sampling and its impact on the estimated disease-exposure association when the exposure is cluster level and measured without error.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results:<\/jats:title>\n                    <jats:p>When the probability of disease varies by exposure status, outcome misclassification at the cluster level is differential under partial-cluster sampling and depends on 1) the partial recording protocol, including the number of observations sampled and the particular sites selected in a cluster; 2) the joint probability structure of the condition within clusters; and 3) the criterion for disease. A numeric example demonstrates that disease-exposure odds ratios under partial-cluster random sampling can be biased in either direction (toward or away from the null) relative to gold-standard odds ratios under full-cluster sampling.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions:<\/jats:title>\n                    <jats:p>In general, misclassification of disease is differential under partial-cluster sampling. In particular, sensitivity and negative predictive values depend on exposure status, which leads to biased inference.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Knowledge Transfer Statement:<\/jats:title>\n                    <jats:p>Partial-mouth sampling causes disease misclassification probabilities, including sensitivity, to vary by exposure groups when disease prevalence differs between groups. As a result, disease-exposure associations may be under- or overestimated by standard analysis procedures for periodontal data relative to full-mouth estimates. Procedures that address bias are needed for partial-recording protocols.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1177\/2380084418781508","type":"journal-article","created":{"date-parts":[[2018,6,12]],"date-time":"2018-06-12T18:53:06Z","timestamp":1528829586000},"page":"388-394","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":5,"title":["Differential Misclassification of Disease under Partial-Mouth Sampling"],"prefix":"10.1177","volume":"3","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7869-2057","authenticated-orcid":false,"given":"J.S.","family":"Preisser","sequence":"first","affiliation":[{"name":"Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"A.E.","family":"Sanders","sequence":"additional","affiliation":[{"name":"Department of Dental Ecology, School of Dentistry, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"R.H.","family":"Lyles","sequence":"additional","affiliation":[{"name":"Department of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University, Atlanta, GA, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"179","published-online":{"date-parts":[[2018,6,12]]},"reference":[{"key":"bibr1-2380084418781508","doi-asserted-by":"publisher","DOI":"10.1111\/jcpe.12425"},{"key":"bibr2-2380084418781508","doi-asserted-by":"publisher","DOI":"10.1111\/j.1600-0765.1970.tb00707.x"},{"key":"bibr3-2380084418781508","doi-asserted-by":"publisher","DOI":"10.1111\/j.1600-0528.2006.00252.x"},{"key":"bibr4-2380084418781508","doi-asserted-by":"publisher","DOI":"10.1111\/biom.12027"},{"key":"bibr5-2380084418781508","doi-asserted-by":"publisher","DOI":"10.1093\/biomet\/93.1.197"},{"key":"bibr6-2380084418781508","doi-asserted-by":"publisher","DOI":"10.1177\/0022034510377793"},{"key":"bibr7-2380084418781508","doi-asserted-by":"publisher","DOI":"10.1111\/j.1600-0528.1987.tb00525.x"},{"key":"bibr8-2380084418781508","doi-asserted-by":"publisher","DOI":"10.1111\/j.1600-051X.2008.01243.x"},{"key":"bibr9-2380084418781508","doi-asserted-by":"publisher","DOI":"10.1007\/s00362-017-0960-2."},{"key":"bibr10-2380084418781508","doi-asserted-by":"publisher","DOI":"10.1111\/j.1600-051X.2008.01222.x"},{"key":"bibr11-2380084418781508","doi-asserted-by":"publisher","DOI":"10.1111\/j.1600-0765.1975.tb00005.x"},{"key":"bibr12-2380084418781508","doi-asserted-by":"publisher","DOI":"10.1902\/jop.2007.060264"},{"key":"bibr13-2380084418781508","doi-asserted-by":"publisher","DOI":"10.1111\/jcpe.12656"},{"key":"bibr14-2380084418781508","doi-asserted-by":"publisher","DOI":"10.1080\/00949655.2013.818148"},{"key":"bibr15-2380084418781508","doi-asserted-by":"publisher","DOI":"10.1111\/j.1541-0420.2007.00956.x"},{"key":"bibr16-2380084418781508","doi-asserted-by":"publisher","DOI":"10.1093\/biomet\/90.2.455"},{"key":"bibr17-2380084418781508","unstructured":"Rothman KJ. 2002. 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