Use of tunnels during Probabilisitic Sensitivity Analysis


I used the "_tunnel" option in my markov model. This worked very well until I wanted to do my PSA. 

I used the _tunnels  in my newly for the PSA designed distributions to depict (for mean or SD) the changing costs or probabilities as well in the PSA. Unfortunetly the _tunnel cannot be used during PSA. Is this due to mistake of me or is this option not valid during PSAs/when using distributions.

Could you help be to find an alternative for using -tunnel states for changing costs/distributions in the PSA?

Thank you in advance.



  • Official comment

    You can Run PSA on a model that references _tunnel. However, tunnel cannot override distribution sampling sequence within PSA. An issue there may be what you are seeing. Note that the same issue would occur with certain types of reference to _stage or _tunnel.

    When PSA runs...

    • The PSA distributions are sampled once.
    • The model is calculated.
    • The prior 2 steps are repeated N times.
    • The overall PSA results are presented based on the N calculations.

    Note that distributions are sampled once per model calculation, not as the model runs (and _stage and _tunnel are incremented).

    GOOD: If you want to sample from different distributions by cycle (from _stage or _tunnel), you need to create different distributions for each cycle and reference them by cycle. Then the proper distribution sample will be used in the analysis even though the distributions were sampled before each model calculation.

    BAD: If you instead try to use the same distribution, but reference _stage or _tunnel within the parameters of the distribution itself, this will not work. It will only use the first value for _stage (0) or _tunnel (1) for the sampling.

    I expect  that you may have used the approach above to try to change a single distribution's parameters by cycle. If you switch to the multiple distributions approach, that will work.

    If you need further support, you can email I created a model to demonstrate the good and bad techniques, but I can't put it in this response. If you create the ticket via the email above, I can send you the model.



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  • I just remembered we have an article in the KnowledgeBase that describes this technique.

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