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Review
. 2017 Oct;37(7):735-746.
doi: 10.1177/0272989X16686559. Epub 2017 Jan 6.

An Overview of R in Health Decision Sciences

Hawre Jalal  1 , Petros Pechlivanoglou  2 , Eline Krijkamp  3 , Fernando Alarid-Escudero  4 , Eva Enns  4 , M G Myriam Hunink  5
Affiliations
Review

An Overview of R in Health Decision Sciences

Hawre Jalal et al. Med Decis Making. 2017 Oct.

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.

Keywords: R project; cost-effectiveness analysis; economic evaluation; literature review.

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Figures

Figure 1
Figure 1
Flow diagram for the literature search. (a) Flow chart of the literature search for articles that used R. (b) Chart of the literature search for articles that used other software, such as SAS, STATA, Microsoft Office Excel, or TreeAge.
Figure 2
Figure 2
Proportion of articles in health decision sciences using the identified software. For comparing R to the other software, we chose to start the x-axis from 1998 because there were only 4 articles that used R in the period between 1994 and 1998.
Figure 3
Figure 3
Cost-effectiveness acceptability curves of a generic cost-effectiveness analysis plotted with ggplot2.
See this image and copyright information in PMC

References

    1. Tosh J, Wailoo A. Review of Software for Decision Modelling. Sheffield, UK: Decision Support Unit, University of Sheffield; 2008. - PubMed
    1. Williams C, Lewsey JD, Briggs AH, Mackay DF. Cost-effectiveness analysis in R using a multi-state modelling survival analysis framework: a tutorial. Med Decis Making. In press. - PMC - PubMed
    1. Hawkins N, Sculpher M, Epstein D. Cost-effectiveness analysis of treatments for chronic disease: using R to incorporate time dependency of treatment response. Med Decis Making. 2005;25(5):511–9. - PubMed
    1. Eddy DM, Hollingworth W, Caro JJ, et al. Model transparency and validation: a report of the ISPOR-SMDM Modeling Good Research Practices Task Force-7. Med Decis Making. 2012;32(5):733–43. - PubMed
    1. Briggs AH, Weinstein MC, Fenwick EA, et al. Model parameter estimation and uncertainty analysis: a report of the ISPOR-SMDM Modeling Good Research Practices Task Force Working Group-6. Med Decis Making. 2012;32(5):722–32. - PubMed

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