Explaining and Controlling Regression to the Mean in Longitudinal Research Designs.
This tutorial is concerned with examining how regression to the mean influences research findings in longitudinal studies of clinical populations. In such studies participants are often obtained because of performance that deviates systematically from the population mean and are then subsequently st...
| Publicado en: | Journal of Speech, Language & Hearing Research Vol. 46; no. 6; pp. 1340 - 1352 |
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| Autores principales: | , |
| Formato: | Artículo |
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American Speech-Language-Hearing Association
December 2003
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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=507869491&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 507869491 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 10924388 1SM jtl: Journal of Speech, Language & Hearing Research issn: 10924388 maglogo: N pubinfo: dt: December 2003 vid: 46 iid: 6 pid: 42 pub: American Speech-Language-Hearing Association artinfo: ui: 507869491 10.1044/1092-4388(2003/104) ppf: 1340 ppct: 12 formats: fmt: – @attributes: type: T – @attributes: type: P size: 5.4MB tig: atl: Explaining and Controlling Regression to the Mean in Longitudinal Research Designs. aug: au: Zhang, Xuyang Tomblin, J. Bruce su: Regression analysis Experimental design Psychological research Psycholinguistics sug: subj: Regression analysis Experimental design Psychological research Psycholinguistics ab: This tutorial is concerned with examining how regression to the mean influences research findings in longitudinal studies of clinical populations. In such studies participants are often obtained because of performance that deviates systematically from the population mean and are then subsequently studied with respect to change in the trait used for this selection. It is shown that in such research there is a potential for the estimates of change to be erroneous due to the effect of regression to the mean. The source of the regression effect is shown to arise from measurement error and a sampling bias of this measurement error in the process of selecting on extreme scores. It is also shown that regression effects are greater with measures that are less reliable and with samples that are selected with more extreme scores. Furthermore, it is shown that regression effects are particularly prominent when measures of change are based on changes in dichotomous states formed from quantitative, normally distributed traits. In addition to a formal analysis of the regression to the mean, the features of regression to the mean are demonstrated via a simulation. 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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