Compound optimal design criteria for nonlinear models

Journal of Biopharmaceutical Statistics

Volumn 18, Issue 4, 2008, Pages 646-661

  McGree, J M ^a   Eccleston, J A ^a   Duffull, S B ^b  

^a UNIVERSITY OF QUEENSLAND   (Australia)

^b UNIVERSITY OF OTAGO   (New Zealand)

Author keywords

Compound criteria; D optimality; Nonlinear models; Opposing criteria; P optimality; T optimality

Indexed keywords

ALGORITHM; ARTICLE; NONLINEAR SYSTEM; PHARMACOKINETICS; PRIORITY JOURNAL; SIMULATION; STATISTICAL ANALYSIS; STATISTICAL MODEL; TECHNIQUE;

NONLINEAR DYNAMICS; RESEARCH DESIGN;

EID: 46749118850     PISSN: 10543406     EISSN: 15205711     Source Type: Journal    
DOI: 10.1080/10543400802071352     Document Type: Article

References (16)

1. Atkinson, A. (2008). DT-optimum designs for model discrimination and parameter estimation. Journal of Statistical Planning and Inference 138:56-64.
2. Atkinson, A. C., Cox, D. R. (1974). Planning experiments for discriminating between models. Journal of the Royal Statistical Society, Series B (Methodological) 36:321-348. With discussion by Wynn, H. P., Titterington, D. M., Laycock, P. J., Lindley, D. V., Hill, D. H., Herzberg, A. M., Tukey, P. A., O'Hagan, A., Fedorov, V. V., Dickey, J., Kiefer, J., Smith, C. A. B.
3. Atkinson, A. C., Donev, A. N. (1992). Optimum Experimental Designs. Oxford: Oxford University Press Inc.
4. Atkinson, A. C., Fedorov, V. V. (1975a). The design of experiments for discriminating between two rival models. Biometrika 62:57-70.
5. Atkinson, A. C., Fedorov, V. V. (1975b). The design of experiments for discriminating between several models. Biometrika 62:289-303.
6. Corana, A., Marchesi, M., Martini, C., Ridella, S. (1987). Minimizing multimodal functions of continuous variables with the 'simulated annealing' algorithm. ACM Transactions on Mathematical Software 13:262-280.
7. Eccleston, J. A., Chan, B. S. P. (2000). Robust designs for correlated data using multiple objective functions. Research Report, University of Queensland, Department of Mathematics.
8. Eccleston, J. A., Whitaker, D. (1992). On the design of optimal changeover experiments through multi-objective simulated annealing. Statistics and Computing 9(1):37-42.
9. Friberg, L. E., Isbister, G. K., Hackett, P. L., Duffull, S. B. (2005). Pharmacokinetic-pharmacodynamic modelling of QT-prolongation following deliberate self-poisonings with citalopram. In Proceedings: Population Approach Group Europe, ISSN: 1871-6032.
10. McCullagh, P., Nelder, J. A. (1989). Generalized Linear Models. 2nd ed. London: Chapman and Hall.
11. McGree, J. M., Eccleston, J. A. (2008). Probability based optimal design. Australian and New Zealand Journal of Statistics 50:13-28.
12. Uciński, D., Bogacka, B. (2005). T-optimum designs for discriminating between two multiresponse dynamic models. Journal of the Royal Statistical Society. Series B (Methodological) 67(Part 1):3-18.
13. Wakefield, J. (1996). Bayesian individualization via sampling-based methods. Journal of Pharmacokinetics and Biopharmaceutics 24(1):103-131.
14. Waterhouse, T. H. (2005). Optimal Experimental Design for Nonlinear and Generalized Linear Models. Ph.D. thesis, University of Queensland.
15. Waterhouse, T. H., Eccleston, J. A., Duffull, S. B. (2006). Optimal crossover designs for logistic regression models in pharmacodynamics. Journal of Biopharmaceutical Statistics 16:881-894.
16. Woods, D. C., Lewis, S. M., Eccleston, J. A., Russell, K. G. (2006). Designs for generalized linear models with several variables and model uncertainty. Technometrics 48(2):284-292.