Model selection versus model averaging in dose finding studies

Statistics in Medicine

Volumn 35, Issue 22, 2016, Pages 4021-4040

  Schorning, Kirsten ^a   Bornkamp, Björn ^b   Bretz, Frank ^b   Dette, Holger ^a  

^a RUHR UNIVERSITY BOCHUM   (Germany)

^b NOVARTIS PHARMA AG   (Switzerland)

Author keywords

clinical trials; model averaging; model selection; simulation study

Indexed keywords

ANALYSIS OF COVARIANCE; ANALYSIS OF VARIANCE; ARTICLE; BOOTSTRAPPING; CHRONIC OBSTRUCTIVE LUNG DISEASE; DOSE RESPONSE; EFFECT SIZE; FORCED EXPIRATORY VOLUME; HUMAN; MODEL AVERAGING; MODEL SELECTION; PHASE 2 CLINICAL TRIAL (TOPIC); PHASE 3 CLINICAL TRIAL (TOPIC); PROBABILITY; SAMPLE SIZE; SIMULATION; STANDARDIZATION; STATISTICAL MODEL;

EID: 84986000830     PISSN: 02776715     EISSN: 10970258     Source Type: Journal    
DOI: 10.1002/sim.6991     Document Type: Article

References (27)

1. Ting N. Dose Finding in Drug Development. Spinger: New York, 2006.
2. Bretz F, Hsu JC, Pinheiro JC, Liu Y. Dose finding - a challenge in statistics. Biometrical Journal 2008; 50:480–504.
3. Bornkamp B, Bretz F, Dmitrienko A, Enas G, Gaydos B, Hsu C-H, König F, Krams M, Liu Q, Neuenschwander B, Parke T, Pinheiro JC, Roy A, Sax R, Shen F. Innovative approaches for designing and analyzing adaptive dose-ranging trials. Journal of Biopharmaceutical Statistics 2007; 17:965–995.
4. Thomas N. Hypothesis testing and Bayesian estimation using a sigmoid Emax model applied to sparse dose designs. Journal of Biopharmaceutical Statistics 2006; 16:657–677.
5. Dragalin V, Hsuan F, Padmanabhan SK. Adaptive designs for dose-finding studies based on the sigmoid emax model. Journal of Biopharmaceutical Statistics 2007; 17:1051–1070.
6. Bretz F, Pinheiro JC, Branson M. Combining multiple comparisons and modeling techniques in dose-response studies. Biometrics 2005; 61:738–748.
7. Pinheiro JC, Bornkamp B, Glimm E, Bretz F. Model-based dose finding under model uncertainty using general parametric models. Statistics in Medicine 2014; 33:1646–1661.
8. CHMP. Qualification opinion of MCP-Mod as an efficient statistical methodology for model-based design and analysis of Phase II dose finding studies under model uncertainty, 2014. European Medicines Agency, Science Medicines Health, Committee for Medicinal Products for Human Use (CHMP), EMA/CHMP/SAWP/757052/2013 available at http://goo.gl/imT7IT [Accessed on 18 May 2016].
9. Verrier D, Sivapregassam S, Solente AC. Dose-finding studies, mcp-mod, model selection, and model averaging: two applications in the real world. Clinical Trials 2014; 11:476–484.
10. Bornkamp B. Viewpoint: model selection uncertainty, pre-specification and model averaging. Pharmaceutical Statistics 2015; 14(2):79–81.
11. Claeskens G, Hjort NL. Model Selection and Model Averaging, Cambridge Series in Statistical and Probabilistic Mathematics. Cambridge University Press: Cambridge, 2008.
12. Raftery A, Zheng Y. Discussion: performance of bayesian model averaging. Journal of the American Statistical Association 2003; 98:931–938.
13. Breiman L. Bagging predictors. Machine Learning 1996; 24:123–140.
14. Akaike H. A new look at the statistical model identification. IEEE Transactions on Automatic Control 1974; 19:716–723.
15. Hurvich C, Tsai C. Regression and time series model selection in small samples. Biometrika 1989; 76:297–307.
16. Takeuchi K. Distribution of informational statistics and a criterion of model fitting. Suri-Kagaku(Mathematical Sciences) 1976; 153:12–18. In Japanese.
17. Schwarz G. Estimating the dimension of a model. The Annals of Statistics 1978; 6(2):461–464.
18. Wassermann L. Bayesian model selection and model averaging. Journal of Mathematical Psychology 2000; 44:92–107.
19. Draper D. Assessment and propagation of model uncertainty. Journal of Royal Statistical Society. Series B(Methodological) 1995; 57(1):45–97.
20. Hjort NL, Claeskens G. Frequentist model average estimators. Journal of the American Statistical Association 2003; 98:879–899.
21. Buckland ST, Burnham K, Augustin NH. Model selection: an integral part of inference. Biometrics 1997; 53:603–618.
22. Clyde M. Model uncertainty and health effect studies for partculate matter. Environmetrics 2000; 11:745–763.
23. Pukelsheim F. Optimal Design of Experiments. SIAM: Philadelphia, 2006.
24. Bornkamp B, Pinheiro J, Bretz F. Dosefinding: planning and analyzing dose finding experiments, 2015. URL http://CRAN.R-project.org/package=DoseFinding [Accessed on 18 May 2016].
25. Thomas N, Sweeney K, Somayaji V. Meta-analysis of clinical dose-response in a large drug development portfolio. Statistics in Biopharmaceutical Research 2014; 6:302–317.
26. Verkindre C, Fukuchi Y, Flémale A, Takeda A, Overend T, Prasad N, Dolker M. Sustained 24-h efficacy of nva237, a once-daily long-acting muscarinic antagonist, in copd patients. Respiratory Medicine 2010; 104:1482–1489.
27. Bornkamp B, Bretz F, Dette H, Pinheiro J. Response-adaptive dose-finding under model uncertainty. Annals of Applied Statistics 2011; 5(2B):1611–1631.