Josh Errickson

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Josh has academic degrees in both Statistics and Computer Science, with deep experience in statistical methodology and use of statistical software. His areas of interest include causal inference, propensity score matching, multiple regression diagnosis, structural equation modeling, software implementation and general computing concerns.


Brady West

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Brady has extensive experience with regression models for clustered and longitudinal data, and he is the lead author of the book Linear Mixed Models: A Practical Guide Using Statistical Software. He is also a co-author of the book Applied Survey Data Analysis. He has extensive expertise in the design and analysis of sample surveys, data management and regression analysis.


Shyamala Nagaraj

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Shyamala has many years of experience with study design and statistical analysis, with a focus on time series analysis, design of experiments, and regression modeling. She has worked in a variety of disciplines, especially in the social sciences.


Hyungjin Myra Kim

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Myra has extensive experience collaborating with biomedical researchers in a variety of areas including clinical trials and health services research. Her areas of biostatistical expertise include medical decision support, and technology assessment.


Brenda Gillespie

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Brenda has extensive experience as a statistical consultant in biomedical settings, including work with clinical trials and observational data in kidney transplant and dialysis studies. Her methodological expertise includes survival analysis and mixed models.


Chris Andrews

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Chris is a Statistician in the U-M Department of Ophthalmology and Visual Sciences and formerly was faculty at Oberlin College and the State University of New York at Buffalo. He currently is the lead statistician for the Northeast Regional Core of the Women’s Health Initiative and has additional experience as a statistical consultant for Roswell Park Cancer Institute. His areas of expertise include survival analysis, linear and generalized linear modeling, missing data methods, metabolomics, and analysis of administrative claims data.