{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,9]],"date-time":"2026-07-09T00:15:15Z","timestamp":1783556115429,"version":"3.55.0"},"reference-count":40,"publisher":"SAGE Publications","issue":"7","license":[{"start":{"date-parts":[[2026,6,18]],"date-time":"2026-06-18T00:00:00Z","timestamp":1781740800000},"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":["Stat Methods Med Res"],"published-print":{"date-parts":[[2026,7]]},"abstract":"<jats:p>\n                    Maximum likelihood estimates of density function and regression coefficients in the proportional odds regression models are proposed and studied based on event-time data that are either completely or partly interval-censored. A smooth estimate of the survival function is then obtained. Theoretical results indicate that the proposed method enjoys an almost parametric\n                    <jats:inline-formula>\n                      <mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\" display=\"inline\" overflow=\"scroll\">\n                        <mml:msqrt>\n                          <mml:mi>n<\/mml:mi>\n                        <\/mml:msqrt>\n                      <\/mml:math>\n                    <\/jats:inline-formula>\n                    -consistency. Some simulation studies show that the proposed method not only gives density and smooth survival curve estimates but also outperforms the existing semiparametric method in terms of estimating both the regression coefficients and the survival curves for small and medium sample sizes. The proposed method is illustrated by an application to the HIV infection data.\n                  <\/jats:p>","DOI":"10.1177\/09622802261461775","type":"journal-article","created":{"date-parts":[[2026,6,18]],"date-time":"2026-06-18T09:21:38Z","timestamp":1781774498000},"page":"1534-1547","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":0,"title":["Maximum likelihood estimation in proportional odds regression model based on interval-censored event-time data"],"prefix":"10.1177","volume":"35","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4808-7400","authenticated-orcid":false,"given":"Zhong","family":"Guan","sequence":"first","affiliation":[{"name":"Mathematical Sciences, Indiana University South Bend, South Bend, IN USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"179","published-online":{"date-parts":[[2026,6,18]]},"reference":[{"key":"e_1_3_3_2_2","doi-asserted-by":"publisher","DOI":"10.1093\/biomet\/66.3.429"},{"key":"e_1_3_3_3_2","doi-asserted-by":"publisher","DOI":"10.1002\/sim.4780111409"},{"key":"e_1_3_3_4_2","doi-asserted-by":"publisher","DOI":"10.1093\/biomet\/93.2.329"},{"key":"e_1_3_3_5_2","doi-asserted-by":"publisher","DOI":"10.1002\/sim.9893"},{"key":"e_1_3_3_6_2","doi-asserted-by":"publisher","DOI":"10.1111\/j.2517-6161.1972.tb00899.x"},{"key":"e_1_3_3_7_2","doi-asserted-by":"publisher","DOI":"10.1111\/j.2517-6161.1980.tb01109.x"},{"key":"e_1_3_3_8_2","doi-asserted-by":"publisher","DOI":"10.1002\/sim.4780020223"},{"key":"e_1_3_3_9_2","doi-asserted-by":"publisher","DOI":"10.2307\/2347295"},{"key":"e_1_3_3_10_2","first-page":"169","article-title":"Proportional odds model for survival data and estimates using ranks","volume":"33","author":"Pettitt AN","year":"1984","unstructured":"Pettitt AN. Proportional odds model for survival data and estimates using ranks. J R Stat Soc Ser C (Appl Stat) 1984; 33: 169\u2013175.","journal-title":"J R Stat Soc Ser C (Appl Stat)"},{"key":"e_1_3_3_11_2","doi-asserted-by":"publisher","DOI":"10.1214\/aos\/1176350269"},{"key":"e_1_3_3_12_2","first-page":"1","article-title":"Partial likelihood in transformation models with censored data","volume":"15","author":"Dabrowska DM","year":"1988","unstructured":"Dabrowska DM, Doksum KA. Partial likelihood in transformation models with censored data. Scand J Stat Theory Appl 1988; 15: 1\u201323.","journal-title":"Scand J Stat Theory Appl"},{"key":"e_1_3_3_13_2","doi-asserted-by":"publisher","DOI":"10.1023\/A:1009634103154"},{"key":"e_1_3_3_14_2","doi-asserted-by":"publisher","DOI":"10.2307\/2530965"},{"key":"e_1_3_3_15_2","doi-asserted-by":"publisher","DOI":"10.2307\/2530698"},{"key":"e_1_3_3_16_2","doi-asserted-by":"publisher","DOI":"10.1111\/1467-9469.00177"},{"key":"e_1_3_3_17_2","doi-asserted-by":"crossref","unstructured":"Huang J Wellner J. Interval censored survival data: a review of recent progress. In: DY L and TR F (eds.) Proceedings of the first seattle symposium in biostatistics Lecture Notes in Statistics Vol. 123 pp.123\u2013169. New York NY: Springer.","DOI":"10.1007\/978-1-4684-6316-3_8"},{"key":"e_1_3_3_18_2","doi-asserted-by":"publisher","DOI":"10.1080\/01621459.1958.10501452"},{"key":"e_1_3_3_19_2","doi-asserted-by":"publisher","DOI":"10.1111\/j.2517-6161.1976.tb01597.x"},{"key":"e_1_3_3_20_2","doi-asserted-by":"publisher","DOI":"10.1093\/biomet\/75.2.237"},{"key":"e_1_3_3_21_2","doi-asserted-by":"publisher","DOI":"10.1080\/01621459.1997.10474050"},{"key":"e_1_3_3_22_2","doi-asserted-by":"publisher","DOI":"10.1080\/01621459.1997.10474051"},{"key":"e_1_3_3_23_2","doi-asserted-by":"publisher","DOI":"10.1093\/biomet\/85.1.165"},{"key":"e_1_3_3_24_2","doi-asserted-by":"publisher","DOI":"10.1111\/j.0006-341X.2000.00511.x"},{"key":"e_1_3_3_25_2","doi-asserted-by":"publisher","DOI":"10.1111\/j.1541-0420.2010.01532.x"},{"key":"e_1_3_3_26_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-981-10-2594-5_6"},{"key":"e_1_3_3_27_2","doi-asserted-by":"publisher","DOI":"10.1080\/10485252.2016.1163349"},{"key":"e_1_3_3_28_2","doi-asserted-by":"publisher","DOI":"10.1080\/10485252.2017.1374384"},{"key":"e_1_3_3_29_2","first-page":"891","article-title":"Fast nonparametric maximum likelihood density deconvolution using Bernstein polynomials","volume":"31","author":"Guan Z","year":"2021","unstructured":"Guan Z. Fast nonparametric maximum likelihood density deconvolution using Bernstein polynomials. Stat Sin 2021; 31: 891\u2013908.","journal-title":"Stat Sin"},{"key":"e_1_3_3_30_2","doi-asserted-by":"publisher","DOI":"10.1002\/sim.8801"},{"key":"e_1_3_3_31_2","doi-asserted-by":"publisher","DOI":"10.1080\/01621459.1996.10476939"},{"key":"e_1_3_3_32_2","unstructured":"Hastie TJ Tibshirani RJ. Generalized additive models Monographs on Statistics and Applied Probability Vol. 43. Chapman and Hall Ltd. London 1990."},{"key":"e_1_3_3_33_2","doi-asserted-by":"publisher","DOI":"10.18637\/jss.v081.i12"},{"key":"e_1_3_3_34_2","doi-asserted-by":"publisher","DOI":"10.1207\/s15327906mbr0102_10"},{"key":"e_1_3_3_35_2","doi-asserted-by":"publisher","DOI":"10.1080\/02331888.2019.1574299"},{"key":"e_1_3_3_36_2","doi-asserted-by":"publisher","DOI":"10.1007\/BF01398235"},{"key":"e_1_3_3_37_2","doi-asserted-by":"publisher","DOI":"10.18637\/jss.v036.i02"},{"key":"e_1_3_3_38_2","doi-asserted-by":"publisher","DOI":"10.1136\/bmj.289.6445.573"},{"key":"e_1_3_3_39_2","doi-asserted-by":"publisher","DOI":"10.1002\/(SICI)1097-0258(19961030)15:20<2177::AID-SIM345>3.0.CO;2-7"},{"key":"e_1_3_3_40_2","doi-asserted-by":"publisher","DOI":"10.1093\/biomet\/93.3.671"},{"key":"e_1_3_3_41_2","unstructured":"Carstensen B Plummer M Laara E et al. Epi: a package for statistical analysis in epidemiology 2022. https:\/\/CRAN.R-project.org\/package=Epi. R package version 2.47."}],"container-title":["Statistical Methods in Medical Research"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.1177\/09622802261461775","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/full-xml\/10.1177\/09622802261461775","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.1177\/09622802261461775","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,7,8]],"date-time":"2026-07-08T23:25:47Z","timestamp":1783553147000},"score":1,"resource":{"primary":{"URL":"https:\/\/journals.sagepub.com\/doi\/10.1177\/09622802261461775"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,6,18]]},"references-count":40,"journal-issue":{"issue":"7","published-print":{"date-parts":[[2026,7]]}},"alternative-id":["10.1177\/09622802261461775"],"URL":"https:\/\/doi.org\/10.1177\/09622802261461775","relation":{},"ISSN":["0962-2802","1477-0334"],"issn-type":[{"value":"0962-2802","type":"print"},{"value":"1477-0334","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,6,18]]}}}