A Survey of Reporting Practices of Computer Simulation Studies in Statistical Research.
Computer simulation studies represent an important tool for investigating processes difficult or impossible to study using mathematical theory or real data. Hoaglin and Andrews recommended these studies be treated as statistical sampling experiments subject to established principles of design and da...
| Publicado en: | American Statistician Vol. 72; no. 4; pp. 321 - 328 |
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| Autores principales: | , , |
| Formato: | Artículo |
| Publicado: |
Taylor & Francis Ltd
Nov2018
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| Materias: | |
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=133105245&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 133105245 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 00031305 STT jtl: American Statistician issn: 00031305 maglogo: Y pubinfo: dt: Nov2018 vid: 72 iid: 4 pid: 377 pub: Taylor & Francis Ltd artinfo: ui: 133105245 10.1080/00031305.2017.1342692 ppf: 321 ppct: 7 formats: tig: atl: A Survey of Reporting Practices of Computer Simulation Studies in Statistical Research. aug: au: Harwell, Michael Kohli, Nidhi Peralta-Torres, Yadira affil: Department of Educational Psychology, University of Minnesota, Minneapolis, MN su: Computer simulation Statistical sampling Application software Data analysis Surveys sug: subj: Computer simulation Software Publishers Software publishers (except video game publishers) Custom Computer Programming Services Marketing Research and Public Opinion Polling Statistical sampling Application software Data analysis Surveys keyword: Design and data analysis Survey Design and data analysis Survey ab: Computer simulation studies represent an important tool for investigating processes difficult or impossible to study using mathematical theory or real data. Hoaglin and Andrews recommended these studies be treated as statistical sampling experiments subject to established principles of design and data analysis, but the survey of Hauck and Anderson suggested these recommendations had, at that point in time, generally been ignored. We update the survey results of Hauck and Anderson using a sample of studies applying simulation methods in statistical research to assess the extent to which the recommendations of Hoaglin and Andrews and others for conducting simulation studies have been adopted. The important role of statistical applications of computer simulation studies in enhancing the reproducibility of scientific findings is also discussed. The results speak to the state of the art and the extent to which these studies are realizing their potential to inform statistical practice and a program of statistical research. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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