Hester van Eeren

| Chapter 3 3 | 48 References Aos, S., Lieb, R., Mayfield, J., Miller, M., & Pennucci, A. (2004). Benefits and costs of prevention and early intervention programs for youth . Olympia: Washington State Institute for Public Policy. Barrett, B., & Byford, S. (2012). Costs and outcomes of an intervention programme for offenders with personality disorders. The British Journal of Psychiatry, 200 , 336-341. Barton, G. R., Briggs, A. H., & Fenwick, E. A. L. (2008). Optimal cost-effectiveness decisions: The rule of the cost-effectiveness acceptability curve (CEAC), the cost-effectiveness acceptability frontier (CEAF), and the expected value of perfection information (EVPI). Value in Health, 11 , 886-897. Bilcke, J., Beutels, P., Brisson, M., & Jit, M. (2011). Accounting for methodological, structural, and parameter uncertainty in decision-analytic models: A practical guide. Medical Decision Making, 31 , 675-692. Bojke, L., Claxton, K., Sculpher, M., & Palmer, S. (2009). Characterizing structural uncertainty in decision analytic models: A review and application of methods. Value in Health, 12 , 739-749. Briggs, A., Claxton, K., & Sculpher, M. (2006). Decision Modelling for Health Economic Evaluation . New York: Oxford University Press. Briggs, A. H. (2000). Handling uncertainty in cost-effectiveness models. Pharmacoeconomics, 17 , 479- 500. Brouwer, W. B., van Hout, B. A., & Rutten, F. (2000). A fair approach to discounting future effects: Taking a societal perspective. Journal of Health Services Research and Policy, 5 , 114-118. Carlson, J. J., Thariani, R., Roth, J., Gralow, J., Henry, N. L., Esmail, L., . . . Veenstra, D. L. (2013). Value- of-information analysis within stakeholder-driven research prioritization process in a US setting: An application in cancer genomics. Medical Decision Making, 33 , 463-471. Cary, M., Butler, S., Baruch, G., Hickey, N., & Byford, S. (2013). Economic evaluation of Multisystemic Therapy for young people at risk for continuing criminal activity in the UK. PloS ONE, 8 , e61070. Chassin, L., Piquero, A. R., Losoya, S. H., Mansion, A. D., & Schubert, C. A. (2013). Joint consideration of distal and proximal predictors of premature mortality among serious juvenile offenders. Journal of Adolescent Health, 52 , 689-696. Claxton, K. (1999). The irrelevance of inference: a decision-making approach to the stochastic evaluation of health care technologies. Journal of Health Economics, 18 , 341-364. Claxton, K. (2008). Exploring uncertainty in cost-effectiveness analysis. Pharmacoeconomics, 26 , 781- 798. Claxton, K., Neumann, P. J., Araki, S., & Weinstein, M. C. (2001). Bayesian value-of-information analysis. An application to a policy model of Alzheimer's disease. International Journal of Technology Assessment in Health Care, 17 , 38-55. Claxton, K., Palmer, S., Longworth, L., Bojke, L., Griffin, S., McKenna, C., . . . Youn, J. (2012). Informing a decision framework for when NICE should recommend the use of health technologies only in the context of an appropriately designed programme of evidence development. Health Technology Assessment, 16 . Claxton, K., Sculpher, M. J., & Drummond, M. F. (2002). A rational framework for decision making by the National Institute For Clinical Excellence (NICE). The Lancet, 360 , 711-715. Cohen, M. A., & Piquero, A. R. (2009). New evidence on the monetary value of saving a high risk youth. Journal of Quantitative Criminology, 25 , 25-49. Cohen, M. A., Piquero, A. R., & Jennings, W. G. (2010). Studying the costs of crime across offender trajectories. Criminology and Public Policy, 9 , 279-305. Cohen, M. A., Rust, R. T., Steen, S., & Tidd, S. T. (2004). Willingness-to-pay for crime control programs. Criminology, 42 , 89-109. Donker, A., & de Bakker, W. (2012). Vrij na een PIJ. Voorspellende factoren van acceptatie vrijwillige nazorg en recidive na een PIJ-maatregel [In freedom after PIJ. The predictive factors of accepting voluntary after care and recidivism after a PIJ-order] . Leiden, the Netherlands: WODC, Ministerie van Veiligheid en Justitie, Hogeschool Leiden.

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