Print  Close

Complex agent-based vs, simpler conditional probability models: tradeoffs in accuaracy and cost

Abstract Number:

3839 

Submission Type:

Contributed Abstract 

Contributed Abstract Type:

Paper 

Participants:

Georgiy Bobashev (1), Joella Adams (2), Michael Duprey (3)

Institutions:

(1) Research Triangle Institute, N/A, (2) RTI International, Durham, NC, (3) RTI International, N/A

Co-Author(s):

Joella Adams  
RTI International
Michael Duprey  
RTI International

First Author:

Georgiy Bobashev  
Research Triangle Institute

Presenting Author:

Georgiy Bobashev  
Research Triangle Institute

Abstract Text:

Agent-based and microsimulation models can quickly become structurally and computationally complex, and require substantial efforts to build, parameterize, calibrate and validate. Simpler "back of the envelope" models can provide ballpark estimates in a much shorter time but with lower accuracy. We discuss compensations for complex networks and non-linearities in simpler models with practical applications to policy and epidemiology. We show from the examples of policy evaluation studies how simple models could provide the upper and lower boundaries of the estimates and discuss the utility of population averaged (conditional probabilities), microsimulation, and agent-based models and the tradeoffs of accuracy, cost, and complexity.

Keywords:

Agent-based models |Microsimulation models|Model simplification|Population averaged model|Forecasting|Epidemic model

Sponsors:

International Statistical Institute

Tracks:

Miscellaneous

Can this be considered for alternate subtype?

Yes

Are you interested in volunteering to serve as a session chair?

Yes

I have read and understand that JSM participants must abide by the Participant Guidelines.

Yes

I understand that JSM participants must register and pay the appropriate registration fee by June 1, 2024. The registration fee is non-refundable.

I understand