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DCEG Biostatisticians Participate in the Joint Statistical Meeting 2018

, by DCEG Staff

DCEG fellows and staff members presented exciting new statistical methods developed to solve important analytic problems in cancer epidemiology and genetics at the Joint Statistical Meeting in Vancouver, Canada From July 28- August 2, 2018. Their presentations are listed below:

  • Bin Zhu, Lisa Mirabello, Nilanjan Chatterjee – “A subregion-based burden test for simultaneous identification of susceptibility loci and sub-regions within”
  • Sung Duk Kim, Paul Albert – “Bayesian latent class models for identifying biomarkers in circadian patterns”
  • Sung Duk Kim, Paul Albert – “Latent mixtures of functions to characterize the complex exposure relationships of pesticides on cancer incidence”
  • Barry Graubard, Anil Chaturvedi, Joseph Tota, Hormuzd Katki – “Population-based disease risk prediction modeling using national survey, clinical, and registry data: Application to risk prediction for oropharyngeal cancer in the U.S. population”
  • Ana Best, Yaakov Malinovsky, Paul Albert – “Efficient group testing algorithms for disease screening among correlated/clustered individuals: Applications to screening HPV”
  • Hyoyoung Choo-Wasaba, Paul Albert, Bin Zhu – “A hidden Markov modeling approach for identifying tumor subclones in next-generation sequencing studies”
  • Marlena Maziarz, Ruth Pfeiffer, Yunhu Wan, Mitchell Gail – “Using standard microbiome reference groups to simplify beta-diversity analyses and facilitate independent validation”
  • Lingxiao Wang, Barry Graubard, Hormuzd Katki, Yan Li – “A kernel weighting approach to improve population representativeness of epidemiological cohort in the analysis”
  • Andriy Derkach, Ruth Pfeiffer – “Subset testing and analysis of multiple phenotypes”
  • Ruth Pfeiffer, Wei Wang, Efstathia Bura – “New dimension reduction methods for combining longitudinally measured biomarkers”
  • Joshua Sampson, Andriy Derkach, Ruth Pfeiffer – “Mediation with latent variables”
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