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Jin Piao, PhD

Associate Professor of Clinical Population and Public Health Sciences

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Phone +1 626 241 1572
Email [email protected]
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Overview

Dr. Jin Piao is an Associate Professor from the Division of Biostatistics, Department of Population and Public Health Sciences, the University of Southern California. She has been working on the development of methodological approaches that have direct impacts on biomedical applications. Her research interest lies in the areas including clinical trial design and analysis, survival analysis, semiparametric statistical models, and meta-analysis. In addition to statistical methodological research, she has been actively collaborated with physicians and biologists in pediatric solid tumors areas and supported several phases I, II, or III solid tumors clinical trials at Children’s Oncology Group.

Education and Training

  • The University of Texas Health Science Center at Houston — Doctor of Philosophy (Ph.D.) — 08/2017 — Biostatistics
  • University of Toledo — Master's degree — 05/2012 — Mathematics
  • Tongji University — Bachelor of Science (BS) — 08/2010 — Statistics

Research Keywords

  • Biostatistics
  • Clinical Trials
  • Survival Analysis
  • Meta-Analysis

Publications

  • Copas-like selection model to correct publication bias in systematic review of diagnostic test studies. Stat Methods Med Res. 2019 Oct-Nov; 28(10-11):2912-2923.. View in PubMed
  • Semiparametric model and inference for spontaneous abortion data with a cured proportion and biased sampling. Biostatistics. 2018 01 01; 19(1):54-70.. View in PubMed
  • Efficient two-stage designs and proper inference for animal studies. Stat Biosci. 2018 Apr; 10(1):217-232.. View in PubMed
  • Maximum likelihood estimation and EM algorithm of Copas-like selection model for publication bias correction. Biostatistics. 2017 Jul 01; 18(3):495-504.. View in PubMed
  • Tumor Thickness and Mitotic Rate Robustly Predict Melanoma-Specific Survival in Patients with Primary Vulvar Melanoma: A Retrospective Review of 100 Cases. Clin Cancer Res. 2017 04 15; 23(8):2093-2104.. View in PubMed
  • B7-H4 expression in ovarian serous carcinoma: a study of 306 cases. Hum Pathol. 2016 11; 57:1-6.. View in PubMed
  • Recurrent event frailty models reduced time-varying and other biases in evaluating transfusion protocols for traumatic hemorrhage. J Clin Epidemiol. 2016 09; 77:52-59.e1.. View in PubMed
  • A joint latent class model for classifying severely hemorrhaging trauma patients. BMC Res Notes. 2015 Oct 24; 8:602.. View in PubMed
  • A joint latent class analysis for adjusting survival bias with application to a trauma transfusion study. Stat Med. 2016 Jan 15; 35(1):65-77.. View in PubMed
  • Estimating the ratio of multivariate recurrent event rates with application to a blood transfusion study. Stat Methods Med Res. 2017 Aug; 26(4):1969-1981.. View in PubMed

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