Biostatistics Events

Biostatistics Departmental Calendar

Event
Mon 6/1/2020 11:00AM - 1:00PM
Biostatistics Dissertation Defense
Jun Zhang-Interpretable Analysis of Multivariate Functional Data-ONLINE Biostatistics Dissertation Defense
Jun Zhang-Interpretable Analysis of Multivariate Functional Data-ONLINE
Mon 6/1/2020 11:00AM - 1:00PM
** Online/Virtual Event **

Jun Zhang of the Department of Biostatistics defends her dissertation on "Interpretable Analysis of Multivariate Functional Data". 


** Online/Virtual Event **
Sat 8/1/2020 to Thu 8/6/2020
Biostatistics Conference
Joint Statistical Meetings - - JSM 2020, Philadelphia, PA Biostatistics Conference
Joint Statistical Meetings - - JSM 2020, Philadelphia, PA
Sat 8/1/2020 to Thu 8/6/2020


The Joint Statistical Meetings, known simply as "JSM", is the largest gathering of statisticians held annually in North American. Faculty and student presenters from the  Department of Biostatistics regularly participate giving invited talks, contributed talks, and poster presentations. Our students often receive top awards and participate in the affiliated career marketplace at the event.


Sun 3/14/2021 to Wed 3/17/2021
Biostatistics Conference
ENAR 2021 Spring Meeting of the International Biometric Society -- Baltimore Biostatistics Conference
ENAR 2021 Spring Meeting of the International Biometric Society -- Baltimore
Sun 3/14/2021 to Wed 3/17/2021


Meetings of the Eastern North American Region of the International Biometric Society (a.k.a. "ENAR meetings") are held in late March or early April each year and reflect the broad interests of the Society, including both quantitative techniques and application areas. Faculty and student presenters from the Department of Biostatistics regularly participate giving invited talks, contributed talks, and poster presentations.


Sat 8/7/2021 to Thu 8/12/2021
Biostatistics Conference
Joint Statistical Meetings - - JSM 2021, Seattle, WA Biostatistics Conference
Joint Statistical Meetings - - JSM 2021, Seattle, WA
Sat 8/7/2021 to Thu 8/12/2021


The Joint Statistical Meetings, known simply as "JSM", is the largest gathering of statisticians held annually in North American. Faculty and student presenters from the  Department of Biostatistics regularly participate giving invited talks, contributed talks, and poster presentations. Our students often receive top awards and participate in the affiliated career marketplace at the event.


Sun 3/27/2022 to Wed 3/30/2022
Biostatistics Conference
ENAR 2022 Spring Meeting of the International Biometric Society -- Houston Biostatistics Conference
ENAR 2022 Spring Meeting of the International Biometric Society -- Houston
Sun 3/27/2022 to Wed 3/30/2022


Meetings of the Eastern North American Region of the International Biometric Society (a.k.a. "ENAR meetings") are held in late March or early April each year and reflect the broad interests of the Society, including both quantitative techniques and application areas. Faculty and student presenters from the Department of Biostatistics regularly participate giving invited talks, contributed talks, and poster presentations.


Sat 8/6/2022 to Thu 8/11/2022
Biostatistics Conference
Joint Statistical Meetings - - JSM 2022, Washington, DC Biostatistics Conference
Joint Statistical Meetings - - JSM 2022, Washington, DC
Sat 8/6/2022 to Thu 8/11/2022


The Joint Statistical Meetings, known simply as "JSM", is the largest gathering of statisticians held annually in North American. Faculty and student presenters from the  Department of Biostatistics regularly participate giving invited talks, contributed talks, and poster presentations. Our students often receive top awards and participate in the affiliated career marketplace at the event.


Recent Events

Biostatistics Seminar Series

Michael Sohn, University of Pennsylvania

Thursday 1/18 3:30PM - 4:30PM
Public Health Auditorium (G23)

Biostatistics guest speaker, Michael Sohn, University of Pennsylvania, will present, "Statistical Methods in Microbiome Data Analysis."

Microbiome study involves new computational and statistical challenges due to the characteristics of microbiome data: high sparsity, over-dispersion, and high-dimensionality. I am going to present two methods that account for the characteristics of microbiome data: 1) a GLM-based latent variable ordination method and 2) a compositional mediation model.

1) GLM-based latent variable ordination method: Distance-based ordination methods, such as the principal coordinate analysis (PCoA), are incapable of distinguishing between location effect (i.e., the difference in mean) and dispersion effect (i.e., the difference in variation) when there is a strong dispersion effect. In other words, PCoA may falsely display a location effect when there is a strong dispersion effect but no location effect. To resolve this potential problem, I proposed, as an ordination method, a zero-inflated quasi-Poisson factor model whose estimated factor loadings are used to display the similarity of samples.

2) Compositional mediation model: The causal mediation model has been extended to incorporate nonlinearity, treatment-mediation interaction, and multiple mediators. These models, however, are not directly applicable when mediators are components of a composition. I proposed a causal, compositional mediation model utilizing the algebra for compositions in the simplex space and an L1 penalized linear regression for compositional data in high-dimensional settings. The estimators of the direct and indirect (or mediation) effects are defined under the potential outcomes framework to establish causal interpretation. The model involves a novel integration of statistical methods in high dimensional regression analysis, compositional data analysis, and causal inference.

Last Updated On Friday, January 5, 2018 by Kapko, Bernadette E
Created On Friday, January 5, 2018

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