Model parameter estimation and uncertainty: A report of the ISPOR-SMDM modeling good research practices task force-6

Value in Health

Volumn 15, Issue 6, 2012, Pages 835-842

  Briggs, Andrew H ^a   Weinstein, Milton C ^b   Fenwick, Elisabeth A L ^a   Karnon, Jonathan ^c   Sculpher, Mark J ^d   Paltiel, A David ^e  

^a UNIVERSITY OF GLASGOW   (United Kingdom)

^b HARVARD SCHOOL OF PUBLIC HEALTH   (United States)

^c UNIVERSITY OF ADELAIDE   (Australia)

^d UNIVERSITY OF YORK   (United Kingdom)

^e YALE UNIVERSITY SCHOOL OF MEDICINE   (United States)

Author keywords

best practices; heterogeneity; sensitivity analysis; uncertainty analysis; value of information

Indexed keywords

ARTICLE; BAYES THEOREM; CALIBRATION; CONFIDENCE INTERVAL; CORRELATION ANALYSIS; COST EFFECTIVENESS ANALYSIS; EVIDENCE BASED MEDICINE; HEALTH CARE PLANNING; HEALTH CARE POLICY; HUMAN; INFORMATION PROCESSING; INTERNAL CONSISTENCY; MEDICAL DECISION MAKING; MULTIVARIATE ANALYSIS; NOMENCLATURE; NORMAL DISTRIBUTION; OUTCOME ASSESSMENT; PRIORITY JOURNAL; PROBABILITY; QUALITATIVE RESEARCH; QUANTITATIVE ANALYSIS; REGRESSION ANALYSIS; RESEARCH; RESOURCE ALLOCATION; SENSITIVITY ANALYSIS; STATISTICAL MODEL; STATISTICAL PARAMETERS; STOCHASTIC MODEL; UNCERTAINTY;

ADVISORY COMMITTEES; COMPARATIVE EFFECTIVENESS RESEARCH; DECISION MAKING; HEALTH CARE RATIONING; MODELS, STATISTICAL; MODELS, THEORETICAL; UNCERTAINTY;

EID: 84866423931     PISSN: 10983015     EISSN: 15244733     Source Type: Journal    
DOI: 10.1016/j.jval.2012.04.014     Document Type: Article

References (31)

1. J.J. Caro, A.H. Briggs, U. Siebert, K. Kuntz Modeling good research practices - overview: a report of the ISPOR-SMDM modeling good research practices task force-1 Value Health 15 2012 796 803
2. M. Roberts, L. Russel, A.D. Paltiel Conceptualizing a model: A report of the ISPOR-SMDM modeling good research practices task force-2 Value Health 15 6 2012 804 811
3. U. Siebert, O. Alagoz, A.M. Bayoumi State-transition modeling: a report of the ISPOR-SMDM modeling good research practices task force-3 Value Health 15 2012 812 820
4. J. Karnon, J. Stahl, A. Brennan Modeling using discrete event simulation: a report of the ISPOR-SMDM modeling good research practices task force-4 Value Health 15 2012 821 827
5. R. Pitman, D. Fisman, G.S. Zaric Dynamic transmission modeling: a report of the ISPOR-SMDM modeling good research practices task force-5 Value Health 15 2012 828 834
6. D.M. Eddy, W. Hollingworth, J.J. Caro Model transparency and validation: a report of the ISPOR-SMDM modeling good research practices task force-7 Value Health 15 2012 843 850
7. K. Claxton Exploring uncertainty in cost-effectiveness analysis Pharmacoeconomics 26 2008 781 798
8. A. Briggs, M. Sculpher, M.J. Buxton Uncertainty in the economic evaluation of health care technologies: the role of sensitivity analysis Health Econ 3 1994 95 104
9. M.R. Gold, J.E. Siegel, L.B. Russell, M.C. Weinstein Cost-effectiveness in Health and Medicine 2007 Oxford University Press New York
10. M. Brisson, W.J. Edmunds Impact of model, methodological, and parameter uncertainty in the economic analysis of vaccination programs Med Decis Making 26 2006 434 446
11. National Institute for Health and Clinical Excellence Guide to the Methods of Technology Appraisal 2008 National Institute for Health and Clinical Excellence London www.nice.org.uk/media/B52/A7/ TAMethodsGuideUpdatedJune2008. pdf [Accessed December 1, 2012]
12. T. Lumley Network meta-analysis for indirect treatment comparisons Stat Med 21 2002 2313 2324
13. B.S. Everitt The Cambridge Dictionary of Statistics 1998 Cambridge University Press Cambridge
14. A.H. Briggs, M.J. Sculpher, K. Claxton Decision Modelling for Health Economic Evaluation 2006 Oxford University Press Oxford
15. A. O'Hagan, C.E. Buck, A. Daneshkhah Uncertain Judgements: Eliciting Expert Probabilities 2006 John Wiley and Sons Chichester
16. D. Lunn, D. Spiegelhalter, A. Thomas, N. Best The BUGS project: evolution, critique and future directions Stat Med 28 2009 3049 3067
17. A.E. Ades, S. Cliffe Markov chain Monte Carlo estimation of a multi-parameter decision model: consistency of evidence and the accurate assessment of uncertainty Med Decis Making 22 2002 359 371
18. J. Karnon, C. Czoski Murray, K.J. Smith, C. Brand A hybrid cohort individual sampling natural history model of age-related macular degeneration: assessing the cost-effectiveness of screening using probabilistic calibration Med Decis Making 29 2009 304 316
19. J. Karnon, T. Vanni Calibrating models in economic evaluation: a comparison of alternative measures of goodness-of-fit, parameter search strategies, and convergence criteria Pharmacoeconomics 29 2011 51 62
20. J.J. Kim, K.M. Kuntz, N.K. Stout Multiparameter calibration of a natural history model of cervical cancer Am J Epidemiol 166 2007 137 150
21. D.C.A. Taylor, V. Pawar, D.T. Kruzikas Incorporating calibrated model parameters into sensitivity analyses: deterministic and probabilistic approaches Pharmacoeconomics 30 2012 119 126
22. T. Vanni, J. Karnon, J. Madan Calibrating models in economic evaluation: a seven step approach Pharmacoeconomics 29 2011 35 49
23. L. Bojke, K. Claxton, M. Sculpher, S. Palmer Characterizing structural uncertainty in decision analytic models: a review and application of methods Value Health 12 2009 739 749
24. C.H. Chapman, S.G. Thompson, L.D. Sharples Accounting for uncertainty in health economic decision models by using model averaging J R Stat Soc Ser A Stat Soc 172 2 2009 383 404
25. C.H. Jackson, L. Bojke, S.G. Thompson A framework for addressing structural uncertainty in decision models Med Decis Making 31 2011 662 674
26. A. Briggs, P. Fenn Confidence intervals or surfaces? Uncertainty on the cost-effectiveness plane Health Econ 7 1998 723 740
27. A.A. Stinnett, J. Mullahy The negative side of cost-effectiveness analysis [letter] JAMA 277 1997 1931 1932
28. K. Claxton, M. Sculpher, M. Drummond A rational framework for decision making by the National Institute for Clinical Excellence (NICE) Lancet 360 2002 711 715
29. A. Brennan, S. Kharroubi, A. O'Hagan Calculating partial expected value of perfect information via Monte Carlo sampling algorithms Med Decis Making 27 2007 448 470
30. B. Groot Koerkamp, M.G. Hunink, T. Stijnen, M.C. Weinstein Identifying key parameters in cost-effectiveness analysis using value of information: a comparison of methods Health Econ 4 2006 383 392
31. A.E. Ades, G. Lu, K. Claxton Expected value of sample information calculations in medical decision modeling Med Decis Making 24 2004 207 227