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Biostatistics Seminars

The Biostatistics seminar series includes research-focused talks by division faculty and other guests. All seminars are free and open to faculty, students and staff.

Upcoming and Recent Seminars

Date Speaker Affiliation Title
Sept 17 Murray Clayton University of Wisconsin – Madison Functional Concurrent Linear Regression Models for Spatial Images
Sep 24 Jeff Goldsmith Columbia University Generalized Multilevel Function-on-Scalar Regression and Principal Component Analysis
Oct 1 Wenbin Lu NC State University On Estimation of Optimal Treatment Regimes for Maximizing t-Year Survival Probability
Oct 15 Lindsay Renfro Mayo Clinic Impact of Copula Directional Specification on Multi-trial Evaluation of Surrogate Endpoints
Oct 22 Dean Follmann National Institute of Allergy and Infectious Disease Vaccine Effciacy from the Virion’s Perspective
Nov 5 Felicity Enders Mayo Clinic Currently Unavailable
Dec 3 Shili Lin Ohio State University Robust Partial Likelihood Approach for Detecting Imprinting and Maternal Effects using Case-control Families
«  September  2014 »
Events on September 4, 2014
  • Biostatistics Plan B Presentation
    Starts: 10:00 am
    Ends: September 4, 2014 - 11:00 am
    Location: Mayo Memorial Building, Room A301
    Description: Masters candidate in Biostatistics, Jason Xu, will present "Association Testing with the ADNI Sequence Data"

    Abstract: The whole genome sequence (WGS) data for 812 subjects from Alzheimer’s Disease Neuroimaging Initiative (ADNI) were processed and used for association testing. A gene-based sequence kernel association test (SKAT) and a single variant test were applied. For the gene-based testing by SKAT, none of the 19,219 genes was significant at the Bonferroni-adjusted significance level 2.6 × 10−6. Three genes THOC3, CDX1 and TMEM159 became significant if a less stringent significance level 5 × 10−5 was enforced. For the single variant testing, three common variants (kgp7502018, rs769449 and rs4420638) were found to be associated with the mean (left and right) hippocampal volume at the Bonferroni-adjusted genome-wide significance level 2.1 × 10−8, after 2,379,855 variants (1,293,243 common variants and 1,086,612 rare variants) were scanned. SNPs rs769449 and rs4420638 reside within gene ApoE and APoC1, respectively.
Events on September 17, 2014
  • Biostatistics Seminar
    Starts: 3:30 pm
    Ends: September 17, 2014 - 5:00 pm
    Location: Moos Tower, Room 2-520
    Description: Murray Clayton, of the Department of Statistics at the University of Wisconsin - Madison, will present "Functional Concurrent Linear Regression Models for Spatial Images"

    This work is motivated by a problem in describing forest nitrogen cycling, and a consequent goal of constructing regression models for spatial images. Specifically, I present a functional concurrent linear model (FLCM) with varying coefficients for two-dimensional spatial images. To address overparameterization issues, the parameter surfaces in this model are transformed into the wavelet domain and then sparse representations are found using two different methods: LASSO and Bayesian variable selection. I will also briefly discuss extensions to address missing data problems for colocated spatial images, focusing on Landsat 7 imagery.

    A social tea will be held at 3:00 P.M. in A434 Mayo. All are Welcome.
    For more details contact 612-624-4655 or see
Events on September 24, 2014
  • Biostatistics Seminar
    Starts: 3:30 pm
    Ends: September 24, 2014 - 5:00 pm
    Location: Moos Tower, Room 2-520
    Description: Jeff Goldsmith, of the Department of Biostatistics at Columbia University, will present "Generalized Multilevel Function-on-Scalar Regression and Principal Component Analysis"

    We considers regression models for generalized, multilevel functional responses: functions are generalized in that they follow an exponential family distribution and multilevel in that they are clustered within groups or subjects. This data structure is increasingly common across scientific domains and is exemplified by our motivating example, in which binary curves indicating physical activity or inactivity are observed for nearly six hundred subjects over five days. We use a generalized linear model to incorporate scalar covariates into the mean structure, and decompose subject-specific and subject-day-specific deviations using multilevel functional principal components analysis. Model parameters are estimated in a Bayesian framework using Stan, a programming language that implements a Hamiltonian Monte Carlo sampler. Simulations designed to mimic the application have good estimation and inferential properties with reasonable computation times for moderate datasets, in both cross-sectional and multilevel scenarios; code is publicly available. In the application we identify effects of age and BMI on the time-specific change in probability of being active over a twenty-four hour period.

    A social tea will be held at 3:00 P.M. in A434 Mayo. All are Welcome.
    For more details contact 612-624-4655 or see
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