BEGIN:VCALENDAR VERSION:2.0 PRODID:-//Date iCal//NONSGML kigkonsult.se iCalcreator 2.20.4// METHOD:PUBLISH X-WR-CALNAME;VALUE=TEXT:ÌÇÐÄÔ­´´ BEGIN:VTIMEZONE TZID:America/New_York BEGIN:STANDARD DTSTART:20201101T020000 TZOFFSETFROM:-0400 TZOFFSETTO:-0500 TZNAME:EST END:STANDARD BEGIN:DAYLIGHT DTSTART:20210314T020000 TZOFFSETFROM:-0500 TZOFFSETTO:-0400 TZNAME:EDT END:DAYLIGHT END:VTIMEZONE BEGIN:VEVENT UID:calendar.404826.field_event_date.0@www.wright.edu DTSTAMP:20260219T201631Z CREATED:20201102T185810Z DESCRIPTION:Meet-n-Greet: 3:30 p.m.\, Talk: 4:00 p.m.Speaker: Dr. Sixia Che n\, University of OklahomaTitle: General-purpose multiply robust data inte gration procedure for combining probability and non-probability samplesHos t: Dr. Zheng Xu ABSTRACT:Recently\, there has been an increased interest i n combining probability and nonprobability samples. Non-probability sample are cheaper and quicker to conduct. However\, the resulting estimators ar e vulnerable to bias as the selection probabilities are unknown. To adjust for the potential bias\, estimation procedures based on parametric or non parametric models has been discussed in the literature. The validity of th e resulting estimators depends on the validity of the underlying models. A lso\, nonparametric approaches suffer from the curse of dimensionality and poor efficiency. We propose a data integration approach by combining mult iple outcome regression models and propensity score models. The proposed a pproach can be used for estimating general parameters including totals\, m eans\, distribution functions and percentiles. The resulting estimators ar e multiply robust in the sense that they remain consistent if all but one model are mis specified. The asymptotic properties of point and variance e stimators will be established. The results from a simulation study shows t he benefits of the proposed method in terms of bias and efficiency.SPEAKER BIO:Dr. Sixia Chen is an assistant professor at department of biostatisti cs and epidemiology of University of Oklahoma Health Sciences Center. Dr. Chen got BA degree in Math from Fudan University at China and PhD degree i n Statistics at Iowa State University. His research interests include surv ey sampling\, missing data analysis\, statistical disclosure control\, emp irical likelihood method\, and big data. Dr. Chen had more than 46 publica tions in peer reviewed journals including Biometrika\, Annals of Applied S tatistics\, and Statistica Sinica. He is now serving as the Associate Edit or for Journal of Korean Statistical Society\, Journal of Survey Statistic s and Methodology\, and Scandinavian Journal of Statistics. Dr. Chen is se rving as the director of novel methodology unit of Oklahoma Shared Clinica l and Translational Research at OUHSC. Dr. Chen performed as PI for severa l local and NIH funded projects.Event Webpage: https://wright.webex.com/wr ight/j.php?MTID=mc5a5a66d526d5ca445fa5a683183d0c9 DTSTART;TZID=America/New_York:20201120T153000 DTEND;TZID=America/New_York:20201120T170000 LAST-MODIFIED:20201102T200558Z SUMMARY:Mathematics and Statistics Colloquium URL;TYPE=URI:/events/mathematics-statistics-colloquiu m-25 END:VEVENT END:VCALENDAR