{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,6]],"date-time":"2026-02-06T21:45:14Z","timestamp":1770414314180,"version":"3.49.0"},"reference-count":14,"publisher":"SAGE Publications","issue":"10-11","license":[{"start":{"date-parts":[[2018,9,10]],"date-time":"2018-09-10T00:00:00Z","timestamp":1536537600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"funder":[{"DOI":"10.13039\/100000057","name":"National Institute of General Medical Sciences","doi-asserted-by":"publisher","award":["R01GM108337"],"award-info":[{"award-number":["R01GM108337"]}],"id":[{"id":"10.13039\/100000057","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":[[2019,11]]},"abstract":"<jats:p> Excessive zeros are common in practice and may cause overdispersion and invalidate inferences when fitting Poisson regression models. Zero-inflated Poisson regression models may be applied if there are inflated zeros; however, it is desirable to test if there are inflated zeros before such zero-inflated Poisson models are applied. Assuming a constant probability of being a structural zero in a zero-inflated Poisson regression model, the existence of the inflated zeros may be tested by testing whether the constant probability is zero. In such situations, the Wald, score, and likelihood ratio tests can be applied. Without specifying a zero-inflated Poisson model, He et\u00a0al. recently developed a test by comparing the amount of observed zeros with that expected under the Poisson model. In this paper, we develop a closed form for the test and compare it with the Wald, score, and likelihood ratio tests through simulation studies. The simulation studies show that the test of He et\u00a0al. is the best in controlling type I errors, while the score test generally has the least power among the tests. The tests are illustrated with two real data examples. <\/jats:p>","DOI":"10.1177\/0962280218796253","type":"journal-article","created":{"date-parts":[[2018,9,10]],"date-time":"2018-09-10T10:02:36Z","timestamp":1536573756000},"page":"3123-3141","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":8,"title":["Testing modified zeros for Poisson regression models"],"prefix":"10.1177","volume":"28","author":[{"given":"Yi","family":"Tang","sequence":"first","affiliation":[{"name":"Department of Mathematics, Tulane University, New Orleans, LA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0404-1494","authenticated-orcid":false,"given":"Wan","family":"Tang","sequence":"additional","affiliation":[{"name":"Department of Global Biostatistics and Data Science, School of Public Health and Tropical Medicine, Tulane University New, Orleans, LA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"179","published-online":{"date-parts":[[2018,9,10]]},"reference":[{"key":"bibr1-0962280218796253","doi-asserted-by":"publisher","DOI":"10.1016\/j.jsat.2008.11.008"},{"key":"bibr2-0962280218796253","doi-asserted-by":"publisher","DOI":"10.1186\/1747-597X-9-3"},{"key":"bibr3-0962280218796253","doi-asserted-by":"publisher","DOI":"10.1080\/07350015.1996.10524676"},{"key":"bibr4-0962280218796253","doi-asserted-by":"publisher","DOI":"10.1023\/A:1021594923546"},{"key":"bibr5-0962280218796253","doi-asserted-by":"publisher","DOI":"10.1002\/sim.860"},{"key":"bibr6-0962280218796253","author":"He H","journal-title":"Stat Method Med Res"},{"key":"bibr7-0962280218796253","doi-asserted-by":"publisher","DOI":"10.2307\/2532959"},{"key":"bibr8-0962280218796253","doi-asserted-by":"publisher","DOI":"10.2307\/3315965"},{"key":"bibr9-0962280218796253","doi-asserted-by":"publisher","DOI":"10.1081\/STA-120026576"},{"key":"bibr10-0962280218796253","doi-asserted-by":"publisher","DOI":"10.1016\/S0167-9473(01)00104-9"},{"key":"bibr11-0962280218796253","first-page":"323","volume":"20","author":"Min A","year":"2010","journal-title":"Statistica Sinica"},{"key":"bibr12-0962280218796253","volume-title":"R: a language and environment for statistical computing","author":"R Development Core Team","year":"2011"},{"key":"bibr13-0962280218796253","doi-asserted-by":"publisher","DOI":"10.1201\/b12123"},{"key":"bibr14-0962280218796253","doi-asserted-by":"publisher","DOI":"10.1097\/NNR.0000000000000071"}],"container-title":["Statistical Methods in Medical Research"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.1177\/0962280218796253","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/full-xml\/10.1177\/0962280218796253","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.1177\/0962280218796253","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,3,3]],"date-time":"2025-03-03T19:38:32Z","timestamp":1741030712000},"score":1,"resource":{"primary":{"URL":"https:\/\/journals.sagepub.com\/doi\/10.1177\/0962280218796253"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,9,10]]},"references-count":14,"journal-issue":{"issue":"10-11","published-print":{"date-parts":[[2019,11]]}},"alternative-id":["10.1177\/0962280218796253"],"URL":"https:\/\/doi.org\/10.1177\/0962280218796253","relation":{},"ISSN":["0962-2802","1477-0334"],"issn-type":[{"value":"0962-2802","type":"print"},{"value":"1477-0334","type":"electronic"}],"subject":[],"published":{"date-parts":[[2018,9,10]]}}}