An Overview of R in Health Decision Sciences.
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...
| Publicado en: | Medical Decision Making Vol. 37; no. 7; pp. 735 - 747 |
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| Autores principales: | , , , , , |
| Formato: | research systematic review tables/charts Journal Article |
| Publicado: |
Sage Publications Inc.
Oct2017
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=125102838&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 125102838 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 0272989X DKI jtl: Medical Decision Making issn: 0272989X maglogo: Y pubinfo: dt: Oct2017 vid: 37 iid: 7 pid: 344 pub: Sage Publications Inc. place: Thousand Oaks, California artinfo: ui: 125102838 125102838 125102838 10.1177/0272989X16686559 125102838 ppf: 735 ppct: 12 formats: tig: atl: An Overview of R in Health Decision Sciences. aug: au: Jalal, Hawre Pechlivanoglou, Petros Krijkamp, Eline Alarid-Escudero, Fernando Enns, Eva Hunink, M. G. Myriam affil: The Hospital for Sick Children, Toronto and University of Toronto, Toronto, Ontario, Canada (PP) sug: subj: Education, Health Sciences Decision Making Decision Support Techniques Systematic Review Software Design Models, Statistical Computer-Aided Design Programming Languages Data Analysis Software Human 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. pubtype: Academic Journal doctype: research systematic review tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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