{"44191":{"#nid":"44191","#data":{"type":"event","title":"Accelerated Recurrence Time Models","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003EDr. Yijian Huang\u003Cbr \/\u003E\nAssociate Professor\u003Cbr \/\u003E\nDepartment of Biostatistics\u003Cbr \/\u003E\nRollins School of Public Health\u003Cbr \/\u003E\nEmory University \u003C\/strong\u003E\n\u003C\/p\u003E\n\u003Cp\u003E\u003Cem\u003EAccelerated Recurrence Time Models\u003C\/em\u003E\n\u003C\/p\u003E\n\u003Cp\u003EFor the analysis with recurrent events, we propose a generalization of the accelerated failure time model to allow for evolving covariate effects.  These so-called accelerated recurrence time models postulate that time to expected recurrence frequency, upon transformation, is a linear function of covariates with frequency-dependent coefficients. This modeling strategy shares the same spirit as quantile regression. An estimation and inference procedure is developed by generalizing the celebrated Powell\u0027s (1984, 1986) estimator for censored quantile regression. Consistency and asymptotic normality of the proposed estimator are established. An algorithm is devised to attain good computational efficiency. Simulations demonstrate that this proposal performs well under practical settings. This methodology is illustrated in an application to the well-known bladder cancer study.\n\u003C\/p\u003E\n\u003Cp\u003EThis talk is based on joint work with Limin Peng. \u003C\/p\u003E","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"Dr. Yijian Huang\nAssociate Professor\nDepartment of Biostatistics\nRollins School of Public Health\nEmory University","format":"limited_html"}],"field_summary_sentence":[{"value":"ISyE Statistics Series"}],"uid":"27216","created_gmt":"2009-10-12 21:21:41","changed_gmt":"2016-10-08 01:48:11","author":"Ruth Gregory","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2007-11-15T10:00:00-05:00","event_time_end":"2007-11-15T11:00:00-05:00","event_time_end_last":"2007-11-15T11:00:00-05:00","gmt_time_start":"2007-11-15 15:00:00","gmt_time_end":"2007-11-15 16:00:00","gmt_time_end_last":"2007-11-15 16:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"related_links":[{"url":"http:\/\/www2.isye.gatech.edu\/statistics\/seminar_series.php","title":"ISyE Statistics Group"}],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[{"id":"6227","name":"ISyE Stewart School"},{"id":"167190","name":"Statistics Seminar"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cstrong\u003EXiaoming Huo\u003C\/strong\u003E\u003Cbr \/\u003EISyE\u003Cbr \/\u003E\u003Ca href=\u0022mailto:xiaoming.huo@isye.gatech.edu\u0022\u003EContact Xiaoming Huo\u003C\/a\u003E\u003Cbr \/\u003E\u003Cstrong\u003E404-894-2300\u003C\/strong\u003E","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}}}