title: An Overview of R in Health Decision Sciences.
abstract: As the complexity of health decision science applications increases, high-level programming languages are increasingly adopted for statistical analyses and numerical computations. These programming languages facilitate sophisticated modeling, model documentation, and analysis reproducibility. Among the high-level programming languages, the statistical programming framework R is gaining increased recognition. R is freely available, cross-platform compatible, and open source. A large community of users who have generated an extensive collection of well-documented packages and functions supports it. These functions facilitate applications of health decision science methodology as well as the visualization and communication of results. Although R's popularity is increasing among health decision scientists, methodological extensions of R in the field of decision analysis remain isolated. The purpose of this article is to provide an overview of existing R functionality that is applicable to the various stages of decision analysis, including model design, input parameter estimation, and analysis of model outputs.
authors.affiliation: University of Pittsburgh Graduate School of Public Health, Pittsburgh, PA, USA (HJ).
authors.forename: Hawre
authors.initials: H
authors.lastname: Jalal
authors.affiliation: The Hospital for Sick Children, Toronto and University of Toronto, Toronto, Ontario, Canada (PP).
authors.forename: Petros
authors.initials: P
authors.lastname: Pechlivanoglou
authors.affiliation: Erasmus MC, Rotterdam, the Netherlands (EK).
authors.forename: Eline
authors.initials: E
authors.lastname: Krijkamp
authors.affiliation: University of Minnesota School of Public Health, Minneapolis, MN, USA (FA-E, EE).
authors.forename: Fernando
authors.initials: F
authors.lastname: Alarid-Escudero
authors.affiliation: University of Minnesota School of Public Health, Minneapolis, MN, USA (FA-E, EE).
authors.forename: Eva
authors.initials: E
authors.lastname: Enns
authors.affiliation: Erasmus MC, Rotterdam, The Netherlands and Harvard T.H. Chan School of Public Health, Boston, MA, USA (MGMH).
authors.forename: M G Myriam
authors.initials: MGM
authors.lastname: Hunink
mesh_terms: D003362:Cost-Benefit Analysis; D003627:Data Interpretation, Statistical; D003661:Decision Support Techniques; D006801:Humans; D008390:Markov Chains; D015233:Models, Statistical; D011381:Programming Languages; D012984:Software
keywords: R project; cost-effectiveness analysis; economic evaluation; literature review