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multicollinearity |
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multicollinearity [‚məl·tē·kō‚lin·ē′ar·əd·ē] (statistics) A concept in regression analysis describing the situation where, because of the high degree of correlation between two or more independent variables, it is not possible to separate accurately the effect of each individual independent variable upon the dependent variable. How to thank TFD for its existence? Tell a friend about us, add a link to this page, add the site to iGoogle, or visit webmaster's page for free fun content. |
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| 20) were analyzed in a correlation matrix to assess for collinearity; we found that within each sex-and race-defined group, no covariates were multicollinear (i. As shown in Table 1, the vocational skills were interrelated and the vocational outcomes were interrelated, but neither set of skills or outcomes was multicollinear. For both of these subgroups, the "sole Maori" variable had statistically significant explanatory power even when the full set of potentially multicollinear controls was included (see Chapple 2000a, Tables 8 and 9). |
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