Department of Statistics, University of Manitoba

“Random effects covariance matrix modeling for longitudinal data with covariates measurement error”

Date: Thursday, January 24, 2019
Time: 2:45 p.m.
Location: P230 Duff Roblin

Longitudinal data occur frequently in practice such as medical studies and life sciences. Generalized linear mixed models (GLMMs) are commonly used to analyze such data. It is typically assumed that the random effects covariance matrix is constant among subjects in these models. In many situations, however, the correlation structure may differ among subjects and ignoring this heterogeneity can lead to biases in model parameters estimate. Recently, Lee et al. developed a heterogeneous random effects covariance matrix for GLMMs for error-free covariates. Covariates measured with error also happen frequently in the longitudinal data set-up (e.g., blood pressure and cholesterol level). Ignoring this issue in the data may produce bias in model parameters estimate and lead to wrong conclusions. In this work, we propose an approach to properly model the random effects covariance matrix based on covariates in the class of GLMMs, where we also have covariates measured with error. The resulting parameters from the decomposition of random effects covariance matrix have a sensible interpretation and can be easily modeled without the concern of positive definiteness of the resulting estimator. The performance of the proposed approach is evaluated through simulation studies, which show that the proposed method performs very well in terms of bias, mean squared error, and coverage rate. An application of the proposed method is also provided using a longitudinal data from Manitoba follow-up study.

This is a work in collaboration with Mahmoud Torabi.

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Important Dates

January 21: Course Add Date - the last date to add a course in the revision period for Winter term and Winter/Summer term courses

January 21: Deadline to Apply Online to Graduate for Spring 2019 (most students)

Upcoming Seminars

Statistics seminar: Erfanul Hoque: “Random effects covariance matrix modeling for longitudinal data with covariates measurement error” — Thursday, January 24 at 2:45 p.m., P230 Duff Roblin.

Statistics seminar: Shirley E. Mills: “Data Analytics and its Application to the World of Sports” — Wednesday, January 30 at 2:45 p.m., 262 E3 EITC.

Statistics seminar: Yang Wang: “Deep Learning: An Introduction and Recent Advances” — Thursday, February 7 at 2:45 p.m., P230 Duff Roblin.

Statistics seminar: Aleeza Gerstein: “TBA” — Thursday, February 14 at 2:45 p.m., P230 Duff Roblin.

Where are they now?

Taraneh Abarin, Ph.D. (2009)

Lesley Crisostomo Alagar, M.Sc. (2006)