14 1 For Example 11 2 (page 324) on y mental impairment, x1 life events, and x2 SES, the multiple regression model has output SES had a P value of 0 011 in the bivariate model containing only that explanatory variable, and LIFE had a Pvalue of 0 018 in the bivariate model containing only that explanatory variable Select explanatory variables from the set x1, x2, x3 x1x2, with 0 05, (a) Using backward elimination (b) Using forward selection Coef Std Error t Sig (Constant) 28 230 2 174 LIFE SES 12 984 000 103 097 032 029 3 177 003 3 351 002 and the model allowing interaction has output Coef Std Error t Sig (Constant) 26 036649 3 948826 6 594 0 0001 LIFE 0 155865 0 085338 1 826 0 0761 SES 0 060493 0 062675 0 965 0 3409 LIFE SES 0 000866 0 001297 0 668 0 5087

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Question: 14.1. For Example 11.2 (page 324) on y = mental impairment, x1 = life events, and x2 = SES, the multiple regression model has output

14.1. For Example 11.2 (page 324) on y = mental impairment, x1 = life events, and x2 = SES, the multiple regression model has output

Coef. Std. Error t Sig. (Constant) 28.230 2.174 LIFE SES 12.984 .000

SES had a P-value of 0.011 in the bivariate model containing only that explanatory variable, and LIFE had a Pvalue of 0.018 in the bivariate model containing only that explanatory variable. Select explanatory variables from the set x1, x2, x3 = x1x2, with α = 0.05,

(a) Using backward elimination.

(b) Using forward selection.

Coef. Std. Error t Sig. (Constant) 28.230 2.174 LIFE SES 12.984 .000 .103 -.097 .032 .029 3.177 .003 -3.351 .002 and the model allowing interaction has output Coef. Std. Error t Sig (Constant) 26.036649 3.948826 6.594 0.0001 LIFE 0.155865 0.085338 1.826 0.0761 SES -0.060493 0.062675 -0.965 0.3409 LIFE*SES -0.000866 0.001297 -0.668 0.5087

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