Abstract Details
Activity Number:
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458
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Type:
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Invited
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Date/Time:
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Wednesday, August 7, 2013 : 8:30 AM to 10:20 AM
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Sponsor:
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Health Policy Statistics Section
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Abstract - #307345 |
Title:
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Uncertainty Analysis in Population-Based Disease Simulation Models: A Practical Framework
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Author(s):
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Behnam Sharif*+
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Companies:
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University of British Columbia
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Keywords:
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Microsimulation ;
Computer Simulation ;
Disease Modelling ;
Uncertainty Analysis ;
Parameter Uncertainty
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Abstract:
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Even though Uncertainty Analysis (UA) is essential as a part of the validation of population-based disease simulation models, literature is imprecise on how it should be performed. In this study, we provided a practical framework for UA for these models and performed an UA in POHEM-OA, a microsimulation model of Osteoarthritis (OA) for Canadian population. METHODS: We examined guidelines of UA methodologies in simulation models of decision analysis and environmental models. We have also developed a mathematical model for calculating the components involved in UA. Using Latin-hypercube sampling, we have sampled from a multivariate lognormal distribution the values for sex-specific hazard ratios of OA by BMI categories. RESULTS: We included two sources for UA: the Monte Carlo error and the parameters uncertainty . For one day run of a 12G memory, CPU=i7-980 Intel, 3.3 GHz, we have calculated m*=1,000,000 and n*=500 based on the developed algorithm. The sex-specific prevalence of OA in Canada predicted by POHEM including the 95% confidence intervals is produced; in particular, in POHEM-OA, the uncertainty of sex-specific prevalence of OA has been shown to be increasing over time.
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Authors who are presenting talks have a * after their name.
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