{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,4,9]],"date-time":"2025-04-09T21:29:00Z","timestamp":1744234140540,"version":"3.40.3"},"reference-count":34,"publisher":"Wiley","issue":"6","license":[{"start":{"date-parts":[[2024,5,6]],"date-time":"2024-05-06T00:00:00Z","timestamp":1714953600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["12075162","72274152"],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100018542","name":"Natural Science Foundation of Sichuan Province","doi-asserted-by":"publisher","award":["24NSFSC0047"],"id":[{"id":"10.13039\/501100018542","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Quality & Reliability Eng"],"published-print":{"date-parts":[[2024,10]]},"abstract":"Abstract<\/jats:title>When monitoring risk in public health, count data commonly exhibit an excessive number of zero, and the zero\u2010inflated Poisson (ZIP) model is often used to fit this type of data. Most previous methods for monitoring of the ZIP model have focused on the changes in the location parameter and the existence of the scale parameter and usually assumed that the scale parameter is zero in the H<\/jats:italic>0<\/jats:sub> stage. However, in an objective environment, data often have certain fluctuations, meaning that the scale parameter always exists. Therefore, it is more meaningful to monitor the changes in the scale parameter on top of the predefined baseline than to monitor its existence. In this study, we derive a score test statistic based on the generalized Henderson's joint likelihood function, construct a risk\u2010adjusted exponentially weighted moving average (EWMA) control chart to monitor the variability of the random effects variance component in the ZIP mixed\u2010effects model. And the convergence property of the score test statistic is proved through derivation, which shows that the new method has theoretical reliability. The simulation results Indicate that when the scale parameter has different predefined baselines and different variation amplitudes, the proposed method is more effective than the existing RA\u2010ZIP and PR\u2010ZIP control charts. In addition, the proposed method is applied to real data from a Hong Kong hospital for online influenza surveillance to demonstrate its practicability.<\/jats:p>","DOI":"10.1002\/qre.3574","type":"journal-article","created":{"date-parts":[[2024,5,7]],"date-time":"2024-05-07T04:15:17Z","timestamp":1715055317000},"page":"3387-3406","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Control chart for detecting the scale parameter of the zero\u2010inflated Poisson model"],"prefix":"10.1002","volume":"40","author":[{"given":"Aijun","family":"Zhao","sequence":"first","affiliation":[{"name":"College of Mathematics and Physics, Geomathematics Key Labomtory of Sichuan Province Chengdu University of Technology Chengdu China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4792-0264","authenticated-orcid":false,"given":"Liu","family":"Liu","sequence":"additional","affiliation":[{"name":"College of Mathematics and Physics, 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