Detecting Model Dependence in Statistical Inference: A Response.
The article presents information on the need of researchers to be able to more readily identify model dependence to improve their own work and reanalyze data from existing articles and reevaluate statistical results and conclusions. Standard uncertainty measures such as standard errors and confidenc...
| Publicado en: | International Studies Quarterly Vol. 51; no. 1; pp. 231 - 242 |
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| Autores principales: | , |
| Formato: | Artículo |
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Oxford University Press / USA
Mar2007
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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=hlh&AN=24165409&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 24165409 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 00208833 ISQ jtl: International Studies Quarterly issn: 00208833 maglogo: N pubinfo: dt: Mar2007 vid: 51 iid: 1 pid: 622 pub: Oxford University Press / USA artinfo: ui: 24165409 10.1111/j.1468-2478.2007.00449.x ppf: 231 ppct: 11 formats: fmt: @attributes: type: P size: 95KB tig: atl: Detecting Model Dependence in Statistical Inference: A Response. aug: au: King, Gary Zeng, Langche affil: David Florence Professor of Government, Harvard University. Professor of Political Science, University of California, San Diego. su: Research methodology Quantitative research Scientific errors Counterfactuals (Logic) Scientific method sug: subj: Research methodology Quantitative research Scientific errors Counterfactuals (Logic) Scientific method ab: The article presents information on the need of researchers to be able to more readily identify model dependence to improve their own work and reanalyze data from existing articles and reevaluate statistical results and conclusions. Standard uncertainty measures such as standard errors and confidence intervals can often be massively underestimated when counterfactuals are posed too far from available data and lead to high degrees of model dependence. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: Y custom: © 2019 International Studies Association. item: International Studies Quarterly holder: Oxford University Press / USA dt: @attributes: year: 2007 holdings: @attributes: islocal: N |
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