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Personal profile

Research interests

My research is in methods for data with spatial and temporal structure. In particular, I am interested in applications in public health and medicine and in computation for latent Gaussian models.

Education/Academic qualification

Statistics, Doctor of Philosophy, University of Washington

External positions

Senior Research Associate, Lancaster University

Jun 2014Jun 2016

Keywords

  • Statistics
  • Biostatistics
  • Spatial Epidemiology
  • Bayesian Inference

Fingerprint Dive into the research topics where Theresa Smith is active. These topic labels come from the works of this person. Together they form a unique fingerprint.

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Age-period-cohort Models Mathematics
Spatial Statistics Mathematics
Incidence Mathematics
Cancer Mathematics
Random Effects Mathematics
Statistics Engineering & Materials Science
Disease Mapping Mathematics
Wishart Distribution Mathematics

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Projects 2018 2020

KTP with Mayden House Ltd

Smith, T. & Faraway, J.

Mayden

9/08/188/12/20

Project: UK industry

Research Output 2015 2019

1 Citation (Scopus)
1 Downloads (Pure)
Open Access
File
Raynaud Disease
Systemic Scleroderma
Physicians
Health
Color

Factors influencing Raynaud’s condition score diary outcomes in systemic sclerosis.

Pauling, J. D., Reilly, E., Smith, T. & Frech, T. M., 1 Mar 2019, In : The Journal of Rheumatology.

Research output: Contribution to journalArticle

9 Citations (Scopus)

A review and comparison of age-period-cohort models for cancer incidence

Smith, T. & Wakefield, J., 19 Jan 2017, In : Statistical Science. 31, 4, p. 591-610

Research output: Contribution to journalArticle

Age-period-cohort Models
Incidence
Cancer
Demography
Identifiability

Ecological Modeling: General Issues

Wakefield, J. C. & Smith, T. R., 4 Apr 2016, Handbook of Spatial Epidemiology. Lawson, A., Banerjee, S., Haining, R. & Ugarte, M. D. (eds.). Boca Raton, U. S. A.: CRC Press, p. 99-118 (Chapman & Hall/CRC Handbooks of Modern Statistical Methods).

Research output: Chapter in Book/Report/Conference proceedingChapter

Thesis

Generalized Additive Models for Large datasets: spatial-temporal modelling of the UK's Daily Black Smoke (1961 - 2005)

Author: Li, Z., 13 Feb 2019

Supervisor: Shaddick, G. (Supervisor), Smith, T. (Supervisor) & Wood, S. (Supervisor)

Student thesis: Doctoral ThesisPhD

File