Biostatistics Events

Biostatistics Departmental Calendar

Event
Thu 11/21/2019 3:30PM - 4:30PM
Biostatistics Seminar Series
Cancelled - Biostatistics Seminar Biostatistics Seminar Series
Cancelled - Biostatistics Seminar
Thu 11/21/2019 3:30PM - 4:30PM
Public Health Lecture Hall (A115)


Public Health Lecture Hall (A115)
Sun 3/22/2020 to Wed 3/25/2020
Biostatistics Conference
ENAR 2020 Spring Meeting of the International Biometric Society -- JW Marriott Nashville Biostatistics Conference
ENAR 2020 Spring Meeting of the International Biometric Society -- JW Marriott Nashville
Sun 3/22/2020 to Wed 3/25/2020


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 8/1/2020 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 Dissertation Defense

Yuvika Paliwal: "Generalized Linear Mixed Models for Analysis of Cross-correlated Binary Data in..."

Thursday 4/13 10:00AM - 12:00PM
4140 Public Health, Young Seminar Room
Yuvika Paliwal of the Department of Biostatistics defends her dissertation on "Generalized Linear Mixed Models for Analysis of Cross-correlated Binary Data in Multi-reader Studies of Diagnostic Imaging"

Graduate faculty of the University and all other interested parties are invited to attend.


ABSTRACT:
Cross-correlated data occur in multi-sample studies with a fully crossed design. An important type of binary cross-correlated data results from multi-reader diagnostic imaging studies where each of several readers independently evaluates the same sample of subjects for the presence or absence of a specific condition (e.g. disease). Such studies are used during development, optimization and regulatory approval of medical technologies, which can eventually be implemented for diagnostics and screening in clinical practice. The analysis of the fully crossed studies can be challenging because of the need to address both reader and subject variability and the related correlation structure. Generalized Linear Mixed Models (GLMM) are implemented in standard statistical software and offer a natural tool for the analysis of the cross-correlated data in the presence of covariates. However, performance of GLMMs in cross-correlated binary data from typical multi-reader studies is generally unknown and is questionable due to the specifics of the available estimation approaches.In the first part of the dissertation we investigate the standard built-in GLMM methods for cross-correlated binary data with and without covariates and explore simple combinations of built-in estimation techniques to overcome existing deficiencies. In the second part, we propose a half-marginal GLMM approach which offers superior interpretation in the context of multi-reader studies of diagnostic accuracy. Our investigation of this model demonstrates good quality of statistical inferences in typical scenarios, but indicates possible large-sample problems stemming from the pseudo-likelihood estimation approach. In the third part of the dissertation we develop an explicit approach for estimating half-marginal model parameters without using pseudo-likelihood. The consistent fixed-effect estimator and its variance are evaluated in a simulation study. The proposed approach can be implemented using non-iterative combination of results from robust GEE models and, for simple scenarios, provides estimates that are equivalent to the empirical estimates.

Last Updated On Friday, July 07, 2017 by Valenti, Renee Nerozzi
Created On Tuesday, March 14, 2017

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