Assessing Statistical Results: Magnitude, Precision, and Model Uncertainty.
Evaluating the importance and the strength of empirical evidence requires asking three questions: First, what are the practical implications of the findings? Second, how precise are the estimates? Confidence intervals provide an intuitive way to communicate precision. Although nontechnical audiences...
| Publicado en: | American Statistician Vol. 73; pp. 118 - 122 |
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| Formato: | Artículo |
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Taylor & Francis Ltd
Mar2019 Supplement
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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=ssf&AN=136176766&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 136176766 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: Mar2019 Supplement vid: 73 pid: 377 pub: Taylor & Francis Ltd artinfo: ui: 136176766 10.1080/00031305.2018.1537889 ppf: 118 ppct: 4 formats: tig: atl: Assessing Statistical Results: Magnitude, Precision, and Model Uncertainty. aug: au: Anderson, Andrew A. affil: Office of the Comptroller of the Currency, U.S. Department of the Treasury, Washington, DC su: Quantitative research Statistical models Statistical reliability Measurement uncertainty (Statistics) Sampling errors sug: subj: Quantitative research Statistical models Statistical reliability Measurement uncertainty (Statistics) Sampling errors keyword: Inference Robustness Sampling error Inference Robustness Sampling error ab: Evaluating the importance and the strength of empirical evidence requires asking three questions: First, what are the practical implications of the findings? Second, how precise are the estimates? Confidence intervals provide an intuitive way to communicate precision. Although nontechnical audiences often misinterpret confidence intervals (CIs), I argue that the result is less dangerous than the misunderstandings that arise from hypothesis tests. Third, is the model correctly specified? The validity of point estimates and CIs depends on the soundness of the underlying model. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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