{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T03:12:59Z","timestamp":1777605179688,"version":"3.51.4"},"reference-count":78,"publisher":"SAGE Publications","issue":"4","license":[{"start":{"date-parts":[[2023,2,14]],"date-time":"2023-02-14T00:00:00Z","timestamp":1676332800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"funder":[{"DOI":"10.13039\/100006093","name":"Patient-Centered Outcomes Research Institute","doi-asserted-by":"publisher","award":["IHS-1507-31640"],"award-info":[{"award-number":["IHS-1507-31640"]}],"id":[{"id":"10.13039\/100006093","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100012464","name":"Kaleida Health Foundation","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100012464","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Stat Methods Med Res"],"published-print":{"date-parts":[[2023,4]]},"abstract":"<jats:p> A useful tool that has gained popularity in the Quality Control area is the control chart which monitors a process over time, identifies potential changes, understands variations, and eventually improves the quality and performance of the process. This article introduces a new class of multivariate semiparametric control charts for monitoring multivariate mixed-type data, which comprise both continuous and discrete random variables (rvs). Our methodology leverages ideas from clustering and Statistical Process Control to develop control charts for MIxed-type data. We propose four control chart schemes based on modified versions of the KAy-means for MIxed LArge KAMILA data clustering algorithm, where we assume that the two existing clusters represent the reference and the test sample. The charts are semiparametric, the continuous rvs follow a distribution that belongs in the class of elliptical distributions. Categorical scale rvs follow a multinomial distribution. We present the algorithmic procedures and study the characteristics of the new control charts. The performance of the proposed schemes is evaluated on the basis of the False Alarm Rate and in-control Average Run Length. Finally, we demonstrate the effectiveness and applicability of our proposed methods utilizing real-world data. <\/jats:p>","DOI":"10.1177\/09622802221142528","type":"journal-article","created":{"date-parts":[[2023,2,15]],"date-time":"2023-02-15T02:22:00Z","timestamp":1676427720000},"page":"671-690","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":2,"title":["Multivariate semiparametric control charts for mixed-type data"],"prefix":"10.1177","volume":"32","author":[{"given":"Elisavet M","family":"Sofikitou","sequence":"first","affiliation":[{"name":"Department of Biostatistics, School of Public Health & Health Professions, State University of New York at Buffalo, Buffalo, NY, USA"},{"name":"The current affiliation of the first author is U.S. Food and Drug Administration (FDA), Center for Devices and Radiological Heath (CDRH), Office of Product Evaluation and Quality (OPEQ). The work was conducted while the first author was a post-doctoral research associate at the University at Buffalo, SUNY."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1453-8229","authenticated-orcid":false,"given":"Marianthi","family":"Markatou","sequence":"additional","affiliation":[{"name":"Department of Biostatistics, School of Public Health & Health Professions, State University of New York at Buffalo, Buffalo, NY, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Markos V","family":"Koutras","sequence":"additional","affiliation":[{"name":"Department of Statistics & Insurance Science, School of Finance & Statistics, University of Piraeus, Pireas, Greece"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"179","published-online":{"date-parts":[[2023,2,14]]},"reference":[{"key":"bibr1-09622802221142528","doi-asserted-by":"publisher","DOI":"10.1002\/j.1538-7305.1926.tb00125.x"},{"key":"bibr2-09622802221142528","doi-asserted-by":"publisher","DOI":"10.1080\/07408179508936797"},{"key":"bibr3-09622802221142528","doi-asserted-by":"publisher","DOI":"10.1002\/qre.730"},{"key":"bibr4-09622802221142528","doi-asserted-by":"publisher","DOI":"10.1080\/16843703.2006.11673124"},{"key":"bibr5-09622802221142528","doi-asserted-by":"publisher","DOI":"10.1002\/qre.829"},{"key":"bibr6-09622802221142528","doi-asserted-by":"publisher","DOI":"10.1080\/16843703.2013.11673306"},{"key":"bibr7-09622802221142528","doi-asserted-by":"publisher","DOI":"10.1201\/b15016"},{"key":"bibr8-09622802221142528","volume-title":"Introduction to statistical quality control","author":"Montgomery D","year":"2020","edition":"8"},{"key":"bibr9-09622802221142528","doi-asserted-by":"publisher","DOI":"10.1080\/00224065.2001.11980081"},{"key":"bibr10-09622802221142528","unstructured":"Chakraborti S, Human SW, Graham MA. 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