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Abstract Details
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Activity Number:
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589
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Type:
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Contributed
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Date/Time:
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Wednesday, August 3, 2011 : 2:00 PM to 3:50 PM
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Sponsor:
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Section on Statistics in Epidemiology
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| Abstract - #302977 |
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Title:
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Uncertainty and Standard Errors in Agent-Based Disease Projections
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Author(s):
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Georgiy Bobashev*+ and R. Joey Morris
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Companies:
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RTI International and RTI International
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Address:
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3040 Cornwallis Rd., Durham , NC, 27709,
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Keywords:
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uncertainty ;
agent-based models ;
longitudinal ;
cross-sectional ;
prediction ;
behavior
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Abstract:
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Agent-based Models (ABMs) can be used to quantify future risks by projecting observable behavior into the future. This can be achieved by simulating a hypothetical longitudinal study based on cross-sectional data and estimating quantities on dynamic risks (e.g., relative hazard). Such an approach, however, requires assessment of the variation of the estimates, which would naturally have a higher variance than would be achieved in a real longitudinal study. We present methodology that considers rigorous statistical measurements such as standard errors and uncertainty associated with the fact that the analyzed longitudinal data are a projection of the cross-sectional survey. We illustrate the use of our approach in simulated and real studies.
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