CORRELATED INDEPENDENT VARIABLES: THE PROBLEM OF MULTICOLLINEARITY.

Whenever two supposedly independent variables are highly correlated, it will be difficult to assess their relative importance in determining some dependent variable. The higher the correlation between independent variables the greater the sampling error of the partials. Numerical examples are given...

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Detalles Bibliográficos
Publicado en:Social Forces Vol. 42; no. 2; pp. 233 - 238
Autores principales: Blalock, H. M., Jr.
Formato: Artículo
Publicado: Oxford University Press / USA Dec63
Materias:
Acceso en línea:Ver este registro en EBSCOhost
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        atl: CORRELATED INDEPENDENT VARIABLES: THE PROBLEM OF MULTICOLLINEARITY.
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          Blalock, H. M.
          Jr.
        affil: Yale University.
      su:
        Multicollinearity
        Mathematical variables
        Statistical correlation
        Sociological research
        Mathematical statistics
        Mathematics
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        subj:
          Multicollinearity
          Mathematical variables
          Statistical correlation
          Sociological research
          Mathematical statistics
          Mathematics
      ab: Whenever two supposedly independent variables are highly correlated, it will be difficult to assess their relative importance in determining some dependent variable. The higher the correlation between independent variables the greater the sampling error of the partials. Numerical examples are given to illustrate the practical implications for social research.
      pubtype: Academic Journal
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    language: English
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