Research

  • Multi-state modelling
  • Survival analysis
  • Medical Statistics
  • Item response modelling

Publications

Statistical

Titman AC, Costain DA, Ridall PG, Gregory K. Joint modelling of goals and bookings in association football. Journal of the Royal Statistical Society, Series A. 2014. To appear.

Titman AC. Estimating parametric semi-Markov models from panel data using phase-type approximations. Statistics & Computing, 2014. 24: 155-164.

Titman AC, Lancaster GA, Colver AF. Item response theory and Structural Equation Modelling for ordinal data: describing the relationship between KIDSCREEN and Life-H. Statistical Methods in Medical Research, 2013.

Titman AC. A pool-adjacent-violators type algorithm for non-parametric estimation of current status data with dependent censoring. Lifetime Data Analysis, 2013. Online First.

Titman AC. Flexible Nonhomogeneous Markov Models for Panel Observed Data. Biometrics, 2011. 67 (3): 780-787. (Supplementary materials document available here.)

Titman AC, Lancaster GA, Carmichael K, Scutt D. Accounting for bias due to a non-ignorable tracing mechanism in a retrospective breast cancer cohort study. Statistics in Medicine. 2011. 30 (4): 324-334.

Titman AC, Sharples LD. Model diagnostics for multi-state models. Statistical Methods in Medical Research. 2010. 19: 621-651.

Titman AC, Sharples LD. Semi-Markov models with phase-type sojourn distributions. Biometrics. 2010. 66 (3): 742-752.

Titman AC. Computation of the asymptotic null distribution of goodness-of-fit tests for multi-state models. Lifetime Data Analysis, 2009. 15 (4): 519-533.

Titman AC, Sharples LD. A general goodness-of-fit test for Markov and hidden Markov models. Statistics in Medicine. 2008. 27: 2177-2195.

Titman AC. Model diagnostics in multi-state models of biological systems. PhD Thesis, University of Cambridge. 2008.

Clinical/Applied

Selinger CP, Andrews JM, Titman A, Norton I, Jones DB, McDonald C, Barr G, Selby W, Leong RW. Long-Term follow up reveals low incidence of colorectal cancer, but frequent need for resection, among Australian patients with inflammatory bowel disease. Clinical Gastroenterology and Hepatology. 2014. 12: 644-650.

Blair J, Lancaster G, Titman A, Peak M, Newland P, Collingwood C, Chesters C, Moorcroft T, Wallin N, Hawcutt D, Gardner C, Didi M, Couriel J. Early morning salivary cortisol and cortisone during inhaled cortiocosteriod therapy in children with asthma. Clinical Endocrinology. 2014. 80:376–383

Deasy C, Titman A, Quinton JN. Measurement of flood peak effects as a result of soil and land management, with focus on experimental issues and scale. Journal of Environmental Management. 2014. 132: 304-312.

Cooper H, Spencer J, Lancaster G, Titman A, Johnson M, Lwin R, Wheeler S, Didi M. Development and psychometric testing of the on-line Adolescent Diabetes Needs Assessment Tool (ADNAT). Journal of Advanced Nursing, 2014. 70 (2) 454-468.

Tan M, Kayani, S, Shaw, B, Dewhurst C, Titman AC, Lancaster GA, Alfirevic Z. Two-year outcomes for infants with low cord pH at birth. Journal of Maternal-Fetal & Neonatal Medicine, 2013. Online First.

McKean K, Key T, Peacock S, Parameshwar J, Taylor CJ, Titman A, Goodman RS. Influence of donor and recipient PECAM-1 and ICAM-1 genotype on the incidence and progression of post-transplant cardiac allograft vasculopathy. International Journal of Immunogenetics. 2010. 37: 415-415.

Titman A, Rogers CA, Bonser RS, Banner NR, Sharples LD. Disease-specific survival benefit of lung transplantation in adults: A national cohort study. American Journal of Transplantation. 2009. 9: 1640-1649. (See also related editorial.)

Pedagogical

Lancaster GA, Titman AC. Using evidence from quantitative studies. In: The Evidence-Based Practice Manual for Nurses (3rd Edition). Editors: Craig JV, Smyth RL, 2012. Elsevier.

Titman AC, Lancaster GA. Personal Response Systems for teaching postgraduate statistics to small groups. Journal of Statistics Education, 2011. 19 (2).

Presentations

March 2014. Robust estimates of state occupancy and transition probabilities for non-Markov multi-state models. International Seminar on Multistate Models, University of Vigo, Spain.

December 2013. Computationally simple state occupancy probability estimation in multi-state models subject to interval censoring. ERCIM 2013, London.

December 2013. Ordinal structural equation modelling of cerebral palsy among European children. Workshop on Using Latent Variables in Health Inequalities Research, University of Manchester.

August 2013. Non-parametric estimation of the survivor function for misclassified failure time data. ISCB 34, Munich.

October 2012. Assessing goodness-of-fit in hidden Markov models. Analyse de Données Longitudinales de Cancer Modèles de Markov Cachés, Toulouse, France.

September 2012. Joint modelling of goals and bookings in association football matches. RSS 2012, Telford.

March 2012. Semi-Markov models under panel observation. Statistics Seminar, University of Kent, Canterbury.

July 2010. Personal Response Systems for teaching postgraduate statistics to small groups. International Conference on Teaching Statistics 8, Ljubljana, Slovenia.

August 2009. Accounting for a non-ignornable tracing mechanism in a breast cancer cohort study. ISCB 30, Prague.

June 2009. Introduction to Personal Response Systems. CETL Seminar Series, Lancaster University.

February 2009. Accounting for informative tracing in a breast cancer cohort study. Lancaster University.

November 2008. Multi-state models: Model diagnostics and model extensions. Lancaster University.

Software and code

R code for fitting non-homogeneous Markov models to panel observed data, using methods described in "Flexible Nonhomogeneous Markov models for panel observed data." Biometrics, 2011.
nhm.zip

R code for fitting semi-parametric models via pseudo-likelihood to competing risks data subject to survival-based tracing, as used in "Accounting for bias due to a non-ignorable tracing mechanism in a retrospective breast cancer cohort study." Statistics in Medicine, 2011.
pseudocomp.R

R code for functions mentioned in "Model diagnostics for multi-state models", SMMR, 2010. For computing "state-change" plots and summary residuals for models fitted using msm:
smmr_code.R

msm: Multi-state Markov and hidden Markov models in continuous time. R package. 2011.
Maintained by Chris Jackson. Contributed to development of functions for model diagnostics.

Contact

Andrew Titman
Department of Mathematics and Statistics
Fylde College
Lancaster University
LA1 4YF

Telephone: (01524) 594475

Email: a.titman@lancaster.ac.uk