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

Benjamin P. Geisler, Uwe Siebert, G. Scott Gazelle, David J. Cohen, Alexander Göhler

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

Objectives: 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. Methods and Results: Using TreeAge Pro Suite 2007 and Microsoft Visual Basic for EXCEL, we constructed a generic script that enables one to perform automated deterministic one-way sensitivity analyses in EXCEL employing microsimulation models. In addition, we constructed a generic EXCEL-worksheet that allows for use of the script with little programming knowledge. Conclusions: Linking TreeAge Pro Suite 2007 and Visual Basic enables the performance of deterministic sensitivity analyses of first-order Monte Carlo simulations. There are other potentially interesting applications for automated analysis.

Original languageEnglish
Pages (from-to)96-97
Number of pages2
JournalValue in Health
Volume12
Issue number1
DOIs
Publication statusPublished - 1 Jan 2009
Externally publishedYes

Keywords

  • Decision analysis model
  • Markov model
  • Methods
  • Microsimulation
  • Modeling

Fingerprint Dive into the research topics of 'Deterministic sensitivity analysis for first-order Monte Carlo simulations: A technical note'. Together they form a unique fingerprint.

  • Cite this