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    Deterministic sensitivity analysis for first-order Monte Carlo simulations: a technical note.

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    Monte Carlo microsimulations have gained increasing popularity in decision-analytic modeling because they can incorporate discrete events. Although deterministic sensitivity analyses are essential for interpretation of results, it remains difficult to combine these alongside Monte Carlo simulations in standard modeling packages without enormous time investment. Our purpose was to facilitate one-way deterministic sensitivity analysis of TreeAge Markov state-transition models requiring first-order Monte Carlo simulations.

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    Description

    Title : Deterministic sensitivity analysis for first-order Monte Carlo simulations: a technical note.
    Author(s) : Benjamin P Geisler, Uwe Siebert, G Scott Gazelle, David J Cohen, Alexander Göhler
    Abstract : Monte Carlo microsimulations have gained increasing popularity in decision-analytic modeling because they can incorporate discrete events. Although deterministic sensitivity analyses are essential for interpretation of results, it remains difficult to combine these alongside Monte Carlo simulations in standard modeling packages without enormous time investment. Our purpose was to facilitate one-way deterministic sensitivity analysis of TreeAge Markov state-transition models requiring first-order Monte Carlo simulations.
    Keywords : computer simulation, humans, monte carlo method, sensitivity specificity, software

    Subject : unspecified
    Area : Other
    Language : English
    Year : 2009

    Affiliations Independent researcher
    Journal : Value in health the journal of the International Society for Pha
    Volume : 12
    Issue : 1
    Publisher : Blackwell Publishing Inc
    Pages : 96-97
    Url : http://dx.doi.org/10.1111/j.1524-4733.2008.00411.x

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