Qualitative Variables in Regression Analysis.
The article focuses on qualitative variables that are used in regression analysis. The behavioral sciences such as education, sociology, psychology and political science generate research data that is often qualitative in nature. The usage of qualitative variables in regression analysis has largely...
| Publicado en: | American Educational Research Journal Vol. 7; no. 4; pp. 541 - 553 |
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| Formato: | Artículo |
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Sage Publications Inc.
Nov1970
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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=18689671&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 18689671 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 00028312 02Y jtl: American Educational Research Journal issn: 00028312 maglogo: Y pubinfo: dt: Nov1970 vid: 7 iid: 4 pid: 344 pub: Sage Publications Inc. artinfo: ui: 18689671 10.3102/00028312007004541 ppf: 541 ppct: 12 formats: tig: atl: Qualitative Variables in Regression Analysis. aug: au: Hurst, Rex L. affil: Department of Applied Statistics-Computer Science, Utah State University, Logan, Utah 84321. su: Regression analysis Mathematical variables Qualitative research Mathematical statistics Dummy variables Mathematical models sug: subj: Regression analysis Mathematical variables Qualitative research Mathematical statistics Dummy variables Mathematical models ab: The article focuses on qualitative variables that are used in regression analysis. The behavioral sciences such as education, sociology, psychology and political science generate research data that is often qualitative in nature. The usage of qualitative variables in regression analysis has largely been handled by ordering the categories into a pseudo-quantitative variable. This procedure is not satisfactory, either in terms of obtaining a realistic model or in terms of interpreting the results. A general least squares approach provides a sound model and the results of the analysis are easy to interpret. The model used is a factorial model with co-variates. The continuous variables are the co-variates and the qualitative variables are the main effects of the factors. Using design variables and writing the continuous variables first, the model may be written as a multiple regression model. The article author has written a group of multiple regression computer programs which includes the capabilities of the foregoing theory. The generation of a dummy variable is controlled by specifying the original variable to be used, the number of categories of the variable and a vector of the codes used. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: Y dt: @attributes: year: 1970 holdings: @attributes: islocal: N |
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