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Procedure for Testing Partial Correlation Coefficients

The partial correlation coefficient testing can be accomplished via the standard six-step method. Let us hold Xi constant and measure the contribution of X2, the humidity, as presented in Example 4.1 (Table 4.5 and Table 4.6). [Pg.209]

Step 3 Write out the computation and test statistic in the sum-of-squares format. We are evaluating X2, so the test statistic is [Pg.209]

As noted earlier, the multiple partial coefficient of determination, r, usually is more of interest than the multiple partial correlation coefficient, because of its direct applicability. That is, an = 0.83 explains 83% of the variability. An r = 0.83 cannot be directly interpreted, except the closer to 0 the value is, the smaller the association the closer r is to 1, the greater the association. The coefficient of determination computation is straightforward. From the model, F = /3o + IB Xi + 2 2 + 3X3 + 4X4, suppose that the researcher wants to compute x x, X2 y or the joint contributiOTi of X3 and X4 to the model with Xi and X2 held constant. The form would be [Pg.210]

However, the multiple partial coefficient of determination generally is not as useful as the F-test. If the multiple partial F-test is used to evaluate the multiple contribution of independent predictor values, while holding the others (in this case Xi, X2) constant, the general formula is [Pg.210]

USED TO DETERMINE HOW MANY x, VARIABLES TO INCLUDE IN THE MODEL [Pg.211]


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