Rate My Professor Ian Harris

Ian R. Harris is an Associate Professor of Mathematical Statistics in the Department of Statistical Science at Southern Methodist University, where he has been on the faculty since 2001. He currently serves as Director of Undergraduate Studies in the department, now known as Statistics and Data Science. Harris earned his Ph.D. in Statistics from the University of Birmingham, England, in 1989, and his B.Sc. in Mathematics from the same institution in 1984. His academic career includes prior positions as Associate Professor of Statistics at Northern Arizona University from 1997 to 2001, Assistant Professor of Mathematics at Northern Arizona University from 1995 to 1997, Visiting Assistant Professor of Statistics at Pennsylvania State University from 1991 to 1992, Assistant Professor of Mathematics at the University of Texas from 1987 to 1995, and Lecturer at Mander Portman Woodward College from 1985 to 1987.

Harris's research specializations encompass hierarchical linear models and associated sampling issues, variance components with a focus on intraclass correlation, mixture models, approximation of special functions, and saddlepoint methods. Additional interests include robust estimation via minimum divergence and density power divergence methods, predictive distributions such as the averaged bootstrap, intraclass correlation coefficient and heritability estimation, random effects models under complex sampling designs, nonstationarity in categorical time series, minimum distance estimation using Hellinger or L2 distances, statistical inference for Poisson mixture models and binomial proportions, and quasi-likelihood for multiplicative random effects. He has authored 36 publications, accumulating over 1,700 citations. Key works include "Robust and efficient estimation by minimising a density power divergence" (1998), which develops robust parameter estimation without nonparametric density estimation; "A Comparison of related density-based minimum divergence estimators" (2001), comparing estimators including maximum likelihood; "Performance of Random Effects Model Estimators Under Complex Sampling Designs" (2011), analyzing estimation in hierarchical models with multistage designs; "The minimum L2 distance estimator for Poisson mixture models" (2011); "Coping with Nonstationarity in Categorical Time Series" (2012); and "A Generalized Divergence for Statistical Inference" (2017), exploring power and density power divergence families for robust inference. Harris's contributions have influenced advancements in statistical modeling and inference.