Multivariate Randomization Tests for Small-N Behavioral Research: A Web-Based Application.
Behavioral research involving statistical analyses of small group data is frequently compromised by conventional parametric statistical procedures. As an alternative, we have developed and deployed several web-based applications that allow behavioral researchers to easily input data on-line and to c...
| Publicado en: | Behavior & Social Issues Vol. 12; no. 1; pp. 64 - 75 |
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| Autores principales: | , , , , |
| Formato: | Artículo |
| Publicado: |
Walden Fellowship, Inc.
Fall/Winter 2002
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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=510268626&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 510268626 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 10649506 G26 jtl: Behavior & Social Issues issn: 10649506 maglogo: N pubinfo: dt: Fall/Winter 2002 vid: 12 iid: 1 pid: 19839 pub: Walden Fellowship, Inc. artinfo: ui: 510268626 ppf: 64 ppct: 11 formats: fmt: – @attributes: type: T – @attributes: type: P size: 290KB tig: atl: Multivariate Randomization Tests for Small-N Behavioral Research: A Web-Based Application. aug: au: Ninness, Chris Rumph, Robin Vasquez, Eleazar Bradfield, Anna Ninness, Sharon K. su: Multivariate analysis Psychological techniques Psychology -- Statistical methods Psychology Computer network resources Statistics sug: subj: Multivariate analysis Psychological techniques Psychology -- Statistical methods Psychology Computer network resources Statistics ab: Behavioral research involving statistical analyses of small group data is frequently compromised by conventional parametric statistical procedures. As an alternative, we have developed and deployed several web-based applications that allow behavioral researchers to easily input data on-line and to calculate levels of significance for small-n studies. Previously, our web-based applications were restricted to parametric and randomization tests involving only one dependent variable. We now have expanded our algorithms such that multivariate analyses may be conducted on sample sizes as small as 6 while employing several dependent measures. This paper provides details for on-line input and interpretation of randomized multivariate statistical tests for small-n studies. Also, to test the power and reliability of our applications, we have compared our multivariate randomization algorithms against a traditional multivariate statistic with two dependent variables. Using Monte Carlo methods, we have assessed the statistical advantages and accuracy of applied multivariate analyses when calculated in both randomized and traditional/parametric formats. Specifically, we have compared probability values for both traditional and randomized MANOVA models by way of Hotelling's T2 and the Randomized multivariate/composite z scores. We discuss the reliability problems associated with using traditional multivariate statistics with small-n studies, and we describe the statistical advantages and some limitations of using our on-line, small-n, multivariate randomization tests. Reprinted by permission of the publisher. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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