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Discovering the causes of cancer and the means of prevention
 

Past Events

  • Various Usage of Influence Functions for Complicated Statistics in the Context of Survey Sampling - Dr. Yu

    Biostatistics Branch Seminar Series

    Seminar: Publicly available national survey data are useful for the evidence-based research to advance our understanding of important questions in the health and biomedical sciences. Dr. Yu discusses methods of appropriate variance estimation.

    March 6, 2020 | 10:30 AM – 11:30 AM
    NCI Shady Grove 7E032/034 Rockville, Maryland
  • From Genome-Wide Association Studies to Biological Insights Using Integrative Molecular Epidemiology - Dr. Kraft

    DCEG Seminar

    Genome-wide association studies (GWAS) have identified thousands of common genetic variants robustly associated with risk of cancer, yet the biological mechanisms underlying these associations remain largely unknown, in part because of confounding by local correlation among variants, and in part because most of these variants are located in non-coding regions with poorly-understood functionality. Methods that integrate GWAS results with auxiliary data can suggest biological hypotheses for further in silico, in vitro and in vivo studies.

    March 5, 2020 | 11:00 AM – 12:00 PM
    NCI Shady Grove TE 406 Rockville, Maryland
  • Next Generation Statistical Methods in the Post-Genome Wide Association Studies - Dr. Chatterjee

    Biostatistics Branch Seminar Series

    In the early years of genome-wide association studies, data analysis primarily relied on fairly simplistic methods, such as running millions of univariate linear or logistic regressions, one for each genetic variant. Recently, however, as the sample sizes for some GWAS have become extremely large and various types of other genomic data have increasingly become available, analysis of such data has also become much more complex and statistically sophisticated.

    March 4, 2020 | 10:30 AM – 11:30 AM
    NCI Shady Grove 6E032/034 Rockville, Maryland
  • Longitudinal Data - Dr. Albert, Part 1 of 3

    Biostatistics at the Frontier Seminar Series

    Part 1 of 3 of the 2020 Biostatistics at the Frontier Seminar Series.

    February 27, 2020 | 10:30 AM – 11:00 AM
    NCI Shady Grove TE 406 Rockville, Maryland
  • Chasing Rainbows: Building a Career in Sexual and Gender Minority Health Equity Science - Dr. Kamen

    Fellows' Cancer Health Disparities Interest Group

    Dr. Kamen's research has focused on factors that lead to health disparities among sexual and gender minority populations, specifically disparities in cancer-related health outcomes and psychological distress

    February 18, 2020 | 10:00 AM – 11:00 AM
    NCI Shady Grove 2E032/034 Rockville, Maryland
  • Statistically Consistent Saliency Estimation - Dr. Barut

    Biostatistics Branch Seminar Series

    February 5, 2020 | 10:30 AM – 11:30 AM
    NCI Shady Grove 6E032/034 Rockville, Maryland
  • Emerging Cancer Health Disparities - Dr. Gomez

    Descriptive Epidemiology Seminar Series

    Dr. Scarlett Lin Gomez is an epidemiologist with research interests in the role of social determinants of health, including race/ethnicity, socioeconomic status, gender, immigration status, sociocultural factors, and neighborhood contextual characteristics, on health outcomes.

    January 23, 2020 | 10:30 AM – 11:30 AM
    NCI Shady Grove Seminar TE406 Rockville, M.D.
  • Diet and Cancer: Harnessing Emerging Technologies to Advance Etiologic Research and Improve Nutritional Assessment - Dr. Loftfield

    DCEG Stadtman Seminar

    Diet and Cancer: Harnessing Emerging Technologies to Advance Etiologic Research and Improve Nutritional Assessment

    January 22, 2020 | 11:00 AM – 12:00 PM
    NCI Shady Grove 2W910/912 Rockville, M.D.
  • Comparing Alternatives for Estimation from Nonprobability Samples - Dr. Valliant

    Biostatistics Branch Seminar Series

    Three approaches to estimation from nonprobability samples are quasi-randomization, superpopulation modeling, and doubly-robust estimation. In the first, the sample is treated as if it was obtained via a probability mechanism but, unlike in probability sampling, that mechanism is unknown. Pseudo selection probabilities of being in the sample are estimated by using the sample in combination with some external data set that covers the desired population.

    January 22, 2020 | 10:30 AM – 11:30 AM
    NCI Shady Grove 1W032/034 Rockville, Maryland
  • Measuring the Mortality Reductions Produced by Organized Cancer Screening: A Principled Approach - Dr. Hanley

    Biostatistics Branch Seminar Series

    In cancer screening trials and population-based comparisons, mortality reductions are usually summarized by an overall (single-number) mortality reduction. This proportional hazards model is logically untenable. I describe a model Liu et al. (IntStatRev2015) for the expected reductions in each (Age,Year) cell of a Lexis diagram.

    January 14, 2020 | 3:00 PM – 4:00 PM
    NCI Shady Grove 6E032/034 Rockville, M.D.