TY - JOUR
T1 - An Overview of R in Health Decision Sciences
AU - Jalal, Hawre
AU - Pechlivanoglou, Petros
AU - Krijkamp, Eline
AU - Alarid-Escudero, Fernando
AU - Enns, Eva
AU - Myriam Hunink, M. G.
N1 - Publisher Copyright:
© 2017 Author(s).
PY - 2017/10/1
Y1 - 2017/10/1
N2 - 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.
AB - 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.
KW - R project
KW - cost-effectiveness analysis
KW - economic evaluation
KW - literature review
UR - http://www.scopus.com/inward/record.url?scp=85027071420&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85027071420&partnerID=8YFLogxK
U2 - 10.1177/0272989X16686559
DO - 10.1177/0272989X16686559
M3 - Article
C2 - 28061043
AN - SCOPUS:85027071420
SN - 0272-989X
VL - 37
SP - 735
EP - 746
JO - Medical Decision Making
JF - Medical Decision Making
IS - 7
ER -