Maximin D-optimal designs for binary longitudinal responses

Computational Statistics and Data Analysis

Volumn 52, Issue 12, 2008, Pages 5253-5262

  Tekle, Fetene B ^a   Tan, Frans E S ^a   Berger, Martijn P F ^a  

^a MAASTRICHT UNIVERSITY   (Netherlands)

Author keywords

[No Author keywords available]

Indexed keywords

EIGENVALUES AND EIGENFUNCTIONS; FOOD PROCESSING; GRAPHICAL USER INTERFACES; MATRIX ALGEBRA; OPTIMAL SYSTEMS; PHOTOACOUSTIC EFFECT;

D OPTIMAL DESIGNS; ELSEVIER (CO); GENERAL (CO); GENERALIZED LINEAR MIXED MODEL (GLMM); INFORMATION MATRIX; LOGISTIC MODELS; MAXIMIN; MIXED EFFECTS MODELS; OPTIMAL DESIGNS; OPTIMAL NUMBER; PARAMETER VALUES; QUASI LIKELIHOOD; REGRESSION PARAMETERS; REPEATED MEASUREMENTS;

OPTIMIZATION;

EID: 47749099261     PISSN: 01679473     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.csda.2008.04.037     Document Type: Article

References (38)

1. Abdelbasit K.M., and Plackett R.L. Experimental design for binary data. J. Amer. Statist. Assoc. 78 (1983) 90-98
2. Atkinson A.C., Chaloner K., Herzberg A.M., and Juritz J. Optimum experimental designs for properties of a compartmental model. Biometrics 49 (1993) 325-337
3. Atkinson A.C., and Donev A.N. Optimal Experimental Designs (1992), Clarendon press, Oxford
4. Braess D., and Dette H. On the number of support points of maximin and Bayesian optimal designs. Ann. Statist. 35 2 (2007) 772-792
5. Breslow N.E., and Clayton D.G. Approximate inference in generalized linear mixed models. J. Amer. Statist. Assoc. 88 (1993) 9-25
6. Carrière I., and Bouyer J. Choosing marginal or random-effects models for longitudinal binary responses: Application to self-reported disability among older persons. BMC Med. Res. Methodology 2 (2002) 15 10.1186/1471-2288-2-15
7. Chaloner K. Bayesian design for estimating the turning point of a quadratic regression. Commun. Stat. Theory Methods 18 4 (1989) 1385-1400
8. Chaloner K., and Larntz K. Optimal Bayesian design applied to logistic regression experiments. J. Statist. Plann. Inference 21 (1989) 191-208
9. Chaloner K., and Verdinelli I. Bayesian experimental design: A review. Statist. Sci. 10 (1995) 273-304
10. Chernoff H. Locally optimal designs for estimating parameters. Ann. Math. Stat. 24 (1953) 586-602
11. Chipman, H., Welch, W., 1996. D-optimal Designs for Generalized Linear Models, unpublished manuscript downloaded from. http://citeseer.ist.psu.edu/144155.html
12. Dargent-Molina P., Faver F., Grandjean H., Baudoin C., Schott A.M., Hausherr E., et al. Fall-related factors and risk of hip fracture: The EPIDOS prospective study. Lancet 348 (1996) 145-149
13. Dette H. Designing of experiments with respect to "standardized" optimality criteria. J. Roy. Stat. Soc. Ser. B 59 (1997) 97-110
14. Dette H. A note on Bayesian C-and D-optimal designs in nonlinear regression models. Ann. Statist. 24 3 (1996) 1225-1234
15. Dette H., and Sahm M. Standardized optimal designs for Binary response experiments. South Afr. Stat. J. 31 (1997) 271-298
16. Dette H., and Sahm M. Minimax optimal designs in nonlinear regression models. Statist. Sinica 8 4 (1998) 1249-1264
17. Fedorov V.V., and Müller W.C. Another view on optimal design for estimating the point of extremum in quadratic regression. Metrika 46 (1997) 147-157
18. Han C., and Chaloner K. Bayesian experimental design for nonlinear mixed-effects models with application to HIV dynamics. Biostatistics 60 (2004) 25-33
19. Imhof L.A. Maximin designs for exponential growth models and heteroscedastic polynomial models. Ann. Statist. 29 (2001) 561-576
20. Khuri A.I., Mukherjee B., Sinha B.K., and Ghosh M. Design issues for generalized linear models: A review. Statist. Sci. 21 (2006) 376-399
21. King J., and Wong W.K. Minimax D-optimal designs for the logistic model. Biometrics 56 4 (2000) 1263-1267
22. Liang K.-Y., and Zeger S.L. Longitudinal data analysis using generalized linear models. Biometrika 73 (1986) 13-22
23. Mathew T., and Sinha B.K. Optimal designs for binary data under logistic regression. J. Statist. Plann. Inference 93 (2001) 295-307
24. McCullagh P., and Nelder J.A. Generalized Linear Models (1989), Chapman & Hall, London
25. Melas V.B., Pepelyshev A., and Cheng R.C.H. Designs for estimating an extremal point of quadratic regression models in a hyperball. Metrika 58 (2003) 193-208
26. Molenberghs G., and Verbeke G. Models for Discrete Longitudinal Data (2005), Springer, New York
27. Müller Ch.H. Maximin efficient designs for estimating nonlinear aspects in linear models. J. Statist. Plann. Inference 44 (1995) 117-132
28. Müller C., and Pazman A. Applications of necessary and sufficient conditions for maximin efficient designs. Metrika 48 (1998) 1-19
29. Ouwens M.J.N.M., Tan F.E.S., and Berger M.P.F. Maximin D-optimal design for longitudinal mixed effects models. Biometrics 58 (2002) 735-741
30. Ouwens M.J.N.M., Tan F.E.S., and Berger M.P.F. A maximin criterion for the logistic random intercept model with covariates. J. Statist. Plann. Inference 136 (2006) 962-981
31. Sebastiani P., and Settimi R. A note on D-optimal designs for a logistic regression model. J. Statist. Plann. Inference 59 (1997) 359-368
32. Silvey S.D. Optimal Design (1980), Chapman and Hall, New York
33. Sitter R.R., and Wu C.F.J. Two-stage design of quantal response studies. Biometrics 55 (1999) 396-402
34. Sitter R.R., and Forbes B.E. Optimal two-stage designs for binary response experiments. Statist. Sinica 7 (1997) 941-955
35. Stiratelli R., Laird N.M., and Ware J.H. Random-effects models for serial observations with binary responses. Biometrics 40 (1984) 961-971
36. Tan F.E.S., and Berger M.P.F. Optimal allocation of time points for the random-effects model. Commun. Stat. Simul. 28 2 (1999) 517-540
37. Wu C.F.J. Efficient sequential designs with binary data. J. Amer. Statist. Assoc. 80 (1985) 974-984
38. Zeger S.L., Liang K.-Y., and Albert P.S. Models for longitudinal data: A generalized estimating equation approach. Biometrics 44 (1988) 1049-1060