2024 |
Tuyl F, Gerlach R, Mengersen K, 'On the Certainty of an Inductive Inference: The Binomial Case', Statistical Science, 39 355-356 (2024) [C1]
In the context of the binomial distribution, the potential need for a prior point mass on ¿ = 0 (1), given x = 0 (n), was identified more than 100 years ago by Jeffreys. Given pre... [more]
In the context of the binomial distribution, the potential need for a prior point mass on ¿ = 0 (1), given x = 0 (n), was identified more than 100 years ago by Jeffreys. Given previous proposals to implement such a point mass, a slightly different approach is proposed, followed by the corresponding posterior probability of "homogeneity" and posterior predictive distribution.
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Open Research Newcastle |
2019 |
Tuyl F, Howley P, 'Bayesian Benefits for Binomial Applications in Practice', Journal of Education, Society and Behavioural Science, 31 1-9 (2019) [C1]
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Open Research Newcastle |
2019 |
Tuyl F, 'A Method to Handle Zero Counts in the Multinomial Model', AMERICAN STATISTICIAN, 73 151-158 (2019) [C1]
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Open Research Newcastle |
2018 |
Lin Y, Howley P, Tuyl F, 'A Posterior Predictive Model-Based Control Chart for Monitoring Healthcare', World Academy of Science, Engineering and Technology International Journal of Electrical and Information Engineering, 12, 793-797 (2018) [C1] |
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Open Research Newcastle |
2017 |
Tuyl FA, 'A note on priors for the multinomial model', American Statistician, 71 298-301 (2017) [C1]
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Open Research Newcastle |
2016 |
Tuyl FA, Howley PP, 'Simplifying Life Through Bayes: Hints for Practitioners New to Bayesian Inference', Quality Management Journal, 23 22-28 (2016) [C1] |
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Open Research Newcastle |
2016 |
Tuyl FA, Gerlach R, Mengersen K, 'Consensus priors for multinomial and binomial ratios', Journal of Statistical Theory and Practice, 10 736-754 (2016) [C1]
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Open Research Newcastle |
2015 |
Bilano V, Gilmour S, Moffiet T, d'Espaignet ET, Stevens GA, Commar A, Tuyl F, Hudson I, Shibuya K, 'Global trends and projections for tobacco use, 1990-2025: an analysis of smoking indicators from the WHO Comprehensive Information Systems for Tobacco Control', LANCET, 385, 966-976 (2015) [C1]
Background Countries have agreed on reduction targets for tobacco smoking stipulated in the WHO global monitoring framework, for achievement by 2025. In an analysis of data for to... [more]
Background Countries have agreed on reduction targets for tobacco smoking stipulated in the WHO global monitoring framework, for achievement by 2025. In an analysis of data for tobacco smoking prevalence from nationally representative survey data, we aimed to provide comprehensive estimates of recent trends in tobacco smoking, projections for future tobacco smoking, and country-level estimates of probabilities of achieving tobacco smoking targets. Methods We used a Bayesian hierarchical meta-regression modelling approach using data from the WHO Comprehensive Information Systems for Tobacco Control to assess trends from 1990 to 2010 and made projections up to 2025 for current tobacco smoking, daily tobacco smoking, current cigarette smoking, and daily cigarette smoking for 173 countries for men and 178 countries for women. Modelling was implemented in Python with DisMod-MR and PyMC. We estimated trends in country-specific prevalence of tobacco use, projections for future tobacco use, and probabilities for decreased tobacco use, increased tobacco use, and achievement of targets for tobacco control from posterior distributions. Findings During the most recent decade (2000-10), the prevalence of tobacco smoking in men fell in 125 (72%) countries, and in women fell in 156 (88%) countries. If these trends continue, only 37 (21%) countries are on track to achieve their targets for men and 88 (49%) are on track for women, and there would be an estimated 1·1 billion current tobacco smokers (95% credible interval 700 million to 1·6 billion) in 2025. Rapid increases are predicted in Africa for men and in the eastern Mediterranean for both men and women, suggesting the need for enhanced measures for tobacco control in these regions. Interpretation Our findings show that striking between-country disparities in tobacco use would persist in 2025, with many countries not on track to achieve tobacco control targets and several low-income and middle-income countries at risk of worsening tobacco epidemics if these trends remain unchanged. Immediate, effective, and sustained action is necessary to attain and maintain desirable trajectories for tobacco control and achieve global convergence towards elimination of tobacco use. Funding Ministry of Health, Labour and Welfare, Japan; Ministry of Education, Culture, Sports and Technology, Japan; Department of Health, Australia; Bloomberg Philanthropies.
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Open Research Newcastle |
2015 |
Howley PP, Hancock SJ, Gibberd RW, Chuang S, Tuyl FA, 'Bayesian methods in reporting and managing Australian clinical indicators', World Journal of Clinical Cases, 3, 625-634 (2015) [C1]
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Open Research Newcastle |
2014 |
Haskins R, Osmotherly PG, Tuyl F, Rivett DA, 'Uncertainty in Clinical Prediction Rules: The Value of Credible Intervals', JOURNAL OF ORTHOPAEDIC & SPORTS PHYSICAL THERAPY, 44, 85-91 (2014) [C1]
SYNOPSIS: Decision making in physical therapy is increasingly informed by evidence in the form of probabilities. Prior beliefs concerning diagnoses, prognoses, and treatment effec... [more]
SYNOPSIS: Decision making in physical therapy is increasingly informed by evidence in the form of probabilities. Prior beliefs concerning diagnoses, prognoses, and treatment effects are quantitatively revised by the integration of new information derived from the history, physical examination, and other investigations in a well-recognized application of Bayes' theorem. Clinical prediction rule development studies commonly employ such methodology to produce quantified estimates of the likelihood of patients having certain diagnoses or achieving given outcomes. To date, the physical therapy literature has been limited to the discussion and calculation of the point estimate of such probabilities. The degree of precision associated with the construction of posterior probabilities, which requires consideration of both uncertainty associated with pretest probability and uncertainty associated with test accuracy, remains largely unrecognized and unreported. This paper provides an introduction to the calculation of the uncertainty interval, known as a credible interval, around posterior probability estimates. The method for calculating the credible interval is detailed and illustrated with example data from 2 clinical prediction rule development studies. Two relatively quick and simple methods for approximating the credible interval are also outlined. It is anticipated that knowledge of the credible interval will have practical implications for the incorporation of probabilistic evidence in clinical practice. Consistent with reporting standards for interventional and diagnostic studies, it is equally appropriate that studies reporting posterior probabilities calculate and report the level of precision associated with these point estimates. Copyright © 2014 Journal of Orthopaedic and Sports Physical Therapy®.
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Open Research Newcastle |
2011 |
Tuyl FA, 'Discussion of 'Integrated objective Bayesian estimation and hypothesis testing' by Bernardo, J.M.', Bayesian Statistics, 48-50 (2011) |
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2010 |
Tuyl FA, Gerlach R, Mengersen K, 'Consensus priors in the presence of general laws', Journal of Applied Probability & Statistics, 5 31-42 (2010) [C1] |
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Open Research Newcastle |
2009 |
Tuyl FA, Gerlach R, Mengersen K, 'Posterior predictive arguments in favor of the Bayes-Laplace prior as the consensus prior for binomial and multinomial parameters', Bayesian Analysis, 4 151-158 (2009) [C1]
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Open Research Newcastle |
2009 |
Tuyl FA, Gerlach R, Mengersen K, ''A comparison of Bayes-Laplace, Jeffreys's, and other priors: The case of zero events;' The American Statistician, 62, 40-44: Comment and reply', American Statistician, 63 197-198 (2009) [C3]
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Open Research Newcastle |
2009 |
Tuyl FA, 'Conditional probability and HIV testing: A real-world example', American Statistician, 63 294 (2009) [C3]
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Open Research Newcastle |
2009 |
Paterson B, Durrheim DN, Tuyl FA, 'Influenza: H1N1 goes to school', Science, 325, 1071-1072 (2009) [C3]
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Open Research Newcastle |
2009 |
Tuyl FA, Gerlach R, Mengersen K, 'The rule of three, its variants and extensions', International Statistical Review, 77 266-275 (2009) [C1]
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Open Research Newcastle |
2009 |
Tuyl F, Gerlach R, Mengersen K, 'Tuyl, F., Gerlach, R., and Mengersen, K. (2008), "A Comparison of Bayes-Laplace, Jeffreys's, and Other Priors: The Case of Zero Events;" The American Statistician, 62, 40-44: Comment and Reply', AMERICAN STATISTICIAN, 63 197-198 (2009) |
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2009 |
Carlson SJ, Dalton CB, Tuyl FA, Durrheim DN, Fejsa J, Muscatello DJ, Francis JL, Tursan D'Espaignet E, 'Flutracking surveillance: Comparing 2007 New South Wales results with laboratory confirmed influenza notifications', Communicable Diseases Intelligence Quarterly Report, 33, 323-326 (2009) [C1]
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Open Research Newcastle |
2009 |
Dalton CB, Durrheim DN, Fejsa J, Francis JL, Carlson S, Tursan D'Espaignet E, Tuyl FA, 'Flutracking: A weekly Australian community online survey of influenza-like illness in 2006, 2007 and 2008', Communicable Diseases Intelligence Quarterly Report, 33, 316-322 (2009) [C1]
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Open Research Newcastle |
2008 |
Cretikos M, Eastwood K, Dalton CB, Merritt TD, Tuyl FA, Winn L, Durrheim DN, 'Household disaster preparedness and information sources: Rapid cluster survey after a storm in New South Wales, Australia', BMC Public Health, 8, 1-9 (2008) [C1]
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Open Research Newcastle |
2008 |
Tuyl FA, Gerlach RH, Mengersen KL, 'A comparison of bayes-laplace, jeffreys, and other priors: the case of zero events', American Statistician, 62 40-44 (2008) [C1]
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Open Research Newcastle |
2008 |
Tuyl FA, Gerlach R, Mengersen K, 'Inference for proportions in a 2 x 2 contingency table: HPD or not HPD?', Biometrics, 64 1293-1295 (2008) [C1]
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2006 |
Gerlach RH, Tuyl FA, 'MCMC methods for comparing stochastic volatility and GARCH models', International Journal of Forecasting, 22, 91-107 (2006) [C1]
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Open Research Newcastle |
2004 |
Easton SA, Gerlach RH, Graham M, Tuyl FA, 'An empirical examination of the pricing of exchange-traded barrier options', The Journal of Futures Market, 24 1049-1064 (2004) [C1]
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Open Research Newcastle |
1998 |
Flanagan K, Colyvas K, Tuyl F, 'Injury after absence: a steel industry study', Journal of Occupational Health and Safety, Australia and New Zealand, 14, 167-178 (1998)
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