Professor Thomas Lumley

BSc(Hons), MSc, PhD

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Chair in Biostatistics

Biography

I attended Monash University (B.Sc.(Hons) in Pure Mathematics), the University of Oxford (M.Sc. in Applied Statistics) and the University of Washington, Seattle (PhD in Biostatistics). I spent twelve years on the faculty of the Department of Biostatistics at the University of Washington, and then moved to Auckland in 2010. I am still an Affiliate Professor at the University of Washington.

Research | Current

My research interests include

  • Semiparametric models
  • Survey sampling
  • Statistical computing
  • Foundations of statistics
  • and whatever methodological problems his medical collaborators come up with -- currently, multiple imputation on big datasets


Resources

  • The survey package for R is a fairly comprehensive system for analysis of data from complex probability samples.
  • I have written a book on survey analysis, published by Wiley.

 

Teaching | Current

  • STATS 765 S1 2020 (with Lisa Chen)
  • STATS 763 S1 2020 (with Alain Vandal)

 

Postgraduate supervision

Potential student projects

  • Likelihood of the empirical distribution function as an approach to Bayesian analysis of survey data.
  • Mixed models under complex sampling -- and maybe network models, too
  • Survey software: design and implementation of various things for the survey package in R or for database backends. Graphics, probability distributions, regression models, multivariate methods...
  • Multiple imputation: implementing more general analysis rules than Rubin's, graphics and exploration
  • Multiple response data: how to work with them in R

Distinctions/Honours

Fellow of the Royal Society of New Zealand
Fellow of the American Statistical Association

Selected publications and creative works (Research Outputs)

  • Holbrook, A., Lumley, T., & Gillen, D. (2019). Estimating prediction error for complex samples. CANADIAN JOURNAL OF STATISTICS-REVUE CANADIENNE DE STATISTIQUE, 48 (2), 204-221. 10.1002/cjs.11527
  • Chen, T., & LUMLEY, T. (2019). Numerical evaluation of methods approximating the distribution of a large quadratic form in normal variables. Computational Statistics and Data Analysis, 139, 75-81. 10.1016/j.csda.2019.05.002
    URL: http://hdl.handle.net/2292/48222
    Other University of Auckland co-authors: Tong Chen
  • Lumley, T. (2019). Fast Generalized Linear Models by Database Sampling and One-Step Polishing. JOURNAL OF COMPUTATIONAL AND GRAPHICAL STATISTICS, 28 (4), 1007-1010. 10.1080/10618600.2019.1610312
  • Fadason, T., Schierding, W., Lumley, T., & O'Sullivan JM (2018). Chromatin interactions and expression quantitative trait loci reveal genetic drivers of multimorbidities. Nature communications, 9 (1)10.1038/s41467-018-07692-y
    URL: http://hdl.handle.net/2292/46205
    Other University of Auckland co-authors: Tayaza Fadason, Justin O'Sullivan, William Schierding
  • Oh, E. J., Shepherd, B. E., Lumley, T., & Shaw, P. A. (2018). Considerations for analysis of time-to-event outcomes measured with error: Bias and correction with SIMEX. Statistics in medicine, 37 (8), 1276-1289. 10.1002/sim.7554
  • Rice, K., Higgins, J. P. T., & Lumley, T. (2018). A re-evaluation of fixed effect(s) meta-analysis. Journal of the Royal Statistical Society. Series A: Statistics in Society, 181 (1), 205-227. 10.1111/rssa.12275
  • Lumley, T., & Scott, A. (2017). Fitting Regression Models to Survey Data. Statistical Science, 32 (2), 265-278. 10.1214/16-STS605
  • Rivera, C., & Lumley, T. (2016). Using the whole cohort in the analysis of countermatched samples. Biometrics, 72 (2), 382-391. 10.1111/biom.12419
    Other University of Auckland co-authors: Claudia Rivera Rodriguez

Contact details

Primary office location

SCIENCE CENTRE - MATHPHYSIC - Bldg 303
Level 3, Room 325
38 PRINCES ST
AUCKLAND 1010
New Zealand