THE RANDOM TOPOLOGY MODEL OF CHANNEL NETWORKS: BIAS IN STATISTICAL TESTS.
Direct tests of the random topology model have traditionally employed the 0.05 level of significance. As exercises in model confirmation, these tests should have used a larger significance level and because they did not, the test have been biased in favor of the model. This bias has contributed to t...
| Publicado en: | Professional Geographer Vol. 38; no. 1; pp. 77 - 82 |
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| Autores principales: | , |
| Formato: | Artículo |
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Taylor & Francis Ltd
Feb86
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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=15547169&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 15547169 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 00330124 PGG jtl: Professional Geographer issn: 00330124 maglogo: Y pubinfo: dt: Feb86 vid: 38 iid: 1 pid: 377 pub: Taylor & Francis Ltd artinfo: ui: 15547169 10.1111/j.0033-0124.1986.00077.x ppf: 77 ppct: 5 formats: tig: atl: THE RANDOM TOPOLOGY MODEL OF CHANNEL NETWORKS: BIAS IN STATISTICAL TESTS. aug: au: Abrahams, Athol D. Mark, David M. affil: State University of New York, Buffalo su: Geographic network analysis Geography -- Methodology Topology Relief models Geography -- Statistical methods Statistical bias sug: subj: Geographic network analysis Geography -- Methodology Topology Relief models Geography -- Statistical methods Statistical bias keyword: channel networks fluvial geomorphology significance tests ab: Direct tests of the random topology model have traditionally employed the 0.05 level of significance. As exercises in model confirmation, these tests should have used a larger significance level and because they did not, the test have been biased in favor of the model. This bias has contributed to the limitations of the model being overlooked. When all published tests of topologically distinct channel networks and ambilateral classes are repeated using a significance level of 0,30 rather than 0.05, the proportion of tests in which the model is rejected increases from 15 to 46 percent. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: Y dt: @attributes: year: 1986 holdings: @attributes: islocal: N |
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