Ken Beath
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Formal Name: Ken Beath Personal Title: Dr Position: Lecturer Organisational Unit: Department of Statistics Telephone: (+61-2) 9850-8516 Email: kbeath@science.mq.edu.au Location: E4A 507
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Research Interests
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Mixture and latent variable models, particularly application to longitudinal data
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Computational methods for latent variable models
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Infant growth modelling
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Order determination for mixture models
Refereed Journal Publications
[1] Kifley, A., Heller, G.Z., Beath, K.J., Bulger, D., Ma, J., and Gebski, V. Multilevel latent variable models for global health-related quality of life assessment. Statistics in Medicine, accepted, 2011.
[2] K.King, P.Douglas, and K.J.Beath. Is premigration health screening worth while?”. accepted, Medical Journal of Australia, 2011.
[3] Karpa, M.J., Gopinath, B., Beath, K., Rochtchina, E., Cumming, R.G., Wang, J.J., and Mitchell, P. Associations between hearing impairment and mortality risk in older persons: the Blue Mountains Hearing Study. Ann Epidemiology, 20(6):452–459, 2010.
[4] Beath, K.J. and Heller, G.Z. Latent trajectory modelling of multivariate binary data. Statistical Modelling, 9(3):199–213, 2009.
[5] Karpa, M.J., Mitchell, P., Beath, K., Rochtchina, E., Cumming, R.G., and Wang, J.J. Direct and indirect effects of visual impairment on mortality risk in older persons. Arch Ophthalmol., 127(10):1347–53, 2009.
[6] Beath, K.J. Infant growth modeling using a shape invariant model with random effects. Statistics in Medicine, 26(12):2547–64, 2007.
[7] Beath, K.J. and Dobson, A.J. Regression to the mean for nonnormal populations. Biometrika, 78(1):431–435, 1991.
Book Chapters
[8] Beath, KJ. Infant growth modelling and assessment of growth. In Preedy VR, editor, The Handbook of Growth and Growth Monitoring in Health and Disease. Springer, accepted.
Conference Publications
[9] Beath, K.J. Application of latent class with random effects models to longitudinal data. International Biometric Society Australasian Region, 2009.
[10] Beath, K.J. and Heller, G.Z. Development of a respiratory illness score using multilevel item response theory models. International Biometric Society Australasian Region, 2007.
[11] Beath, K.J. Latent trajectory modelling of multiple binary data. International Biometric Society, 2006.
[12] Dobson, A.J., Beath, K.J., and Shearer, W. Regression to the mean. In I. Francis, B.F.J. Manly, and F.C-Y. Lam, editors, Proceedings of the Pacific Statistical Congress, pages 62–64. Elsevier, 1985.
Other Publications
[13] Beath, K. J. randomLCA Package, R package for latent class models including random effects, 2008.
[14] Beath, KJ. Modelling of Infant Growth Data. Master of Appl Stat-J Roy St C project, Macquarie University, Sydney, Australia, 2004.
[15] Wlodarczyk, J, Beath, K, and TUNRA. Heavy metals in seafood in Lake Macquarie : a cross-sectional survey. John Wlodarczyk Consulting Services, 1997.
[16] Gibberd, RW, Beath, KJ, Bonett, A, Roder, D, Esterman, A, and Hakulinen, T. Survival of Cancer Patients in South Australia during 1977-1986. University of Newcastle, 1989.
Submitted or In Progress Publications
[17] Beath, K.J. Application of latent class with random effects models to latent trajectory modelling of binary data.
[18] Beath, K.J. Application of multilevel item response theory models to determine the effect of respiratory symptoms on infant growth.