Bryan Shepherd, Chun Li and Qi Liu, The Canadian Journal of Statistics Award 2017

 cjsaward_bryanshepherd.jpg
cjsaward_chunli.jpg
cjsaward_qiliu.jpg
The Canadian Journal of Statistics Award
2017
“Probability-scale residuals for continuous, discrete, and censored data.” (Volume 44, no. 4, pp. 463-479)

The Canadian Journal of Statistics Award is presented each year by the Statistical Society of Canada to the author(s) of an article published in the journal, in recognition of the outstanding quality of the methodological innovation and presentation.

This year’s winner is the article entitled “Probability-scale residuals for continuous, discrete, and censored data.” (Volume 44, no. 4, pp. 463-479) by Bryan E. Shepherd, Chun Li and Qi Liu.


The paper proposes residuals based on a comparison of the two fitted tail probabilities for a response.  These probability scale residuals provide diagnostics for models in which numerical differences in response values are not meaningful or when the expectation of the fitted distribution cannot easily be calculated.  The paper develops the properties of these diagnostics and shows how they can be useful for a wide variety of data types including censored data.

 

Bryan Shepherd is an Associate Professor of Biostatistics at Vanderbilt University Medical Center. He received his PhD in Biostatistics from the University of Washington in 2005.  His research interests can be broadly summarized as developing and applying novel statistical methods to studies of HIV/AIDS, tuberculosis, and other diseases of global health importance.  His statistical methods research has included techniques for analyzing ordinal data, causal inference methods, and approaches for the analysis of error-prone observational data.
 

Chun Li is an Associate Professor of Epidemiology and Biostatistics at Case Western Reserve University. He received his PhD in Biostatistics from the University of Michigan in 2002. His current research in statistics is on ordinal data analysis, linear transformation models, and large-scale data analysis. He has also worked on statistical genetics for nearly two decades, and has developed methods for a wide variety of data and analysis types in human genetics studies, ranging from linkage and association analyses to design and evaluation of genome-wide association studies, and to design and data processing of next-generation sequencing studies. He is currently working on developing methods to efficiently analyze Hi-C data and single-cell RNA-Seq data. 


Qi Liu is a Senior Scientist at Merck & Co., Inc. She received her PhD in Biostatistics from Vanderbilt University in 2016. Her research interests focus on design and analysis of clinical trials, semiparametric regression models, ordered categorical data, and causal inference. 


Bryan Shepherd will present an overview of their work in a special session at this year’s SSC Annual Meeting at the University of Manitoba.

The citation for the award reads: 

The article entitled “Probability-scale residuals for continuous, discrete, and censored data” by Bryan E. Shepherd, Chun Li and Qi Liu is recognized for excellence, creativity, and presentation.