7. For the 2014 GSS, the following table shows estimates (with se values in pare

Question

7. For the 2014 GSS, the following table shows estimates (with se values in parentheses) for four regression models for y = political party iden tification in the United States, scored from 1 = strong Democrat to 7 = strong Republican. The explanatory variables are number of years of education in model 1, also annual income last year (12 ordered cat- egories, scored 1 to 12) in model 2, also religion (1 undamentalist, 2 = moderate, 3 liberal) in model 3, and also political views (scored from 1 extremely liberal to 7 extremely conservative) in model 4 TABLE 11.20 Model I Model 3 se Model 4 se Model 2 Variable se 0.004 (0.013) Education Income Religion Political views Constant -0.015(0.017) -0.003 (0.018) 0010 (0.016) 0.036 (0.018) 0040 (0.018) 0.016 (0.016) 0.255 (0.069) 0.036 (0.061) 0.752 (0.032) 3.597 3.496 .833 0.255 Multiple R 0.007 0.054 0.115 0.550 (a) Summarize what you learn from these four model fits (b) The effect of religion weakens considerably (and even changes direction) after adding political views to the model. Is it plausible that the relationship between y and religion is spurious? Explain.

Explanation / Answer

a) Ans: From the four models we know that by adding the covariates increases the values of R^2. Hence, we can conclude that by adding variables increases the variation explained by the regressors in the model so the model of covariates income, religion, and political views is the best model among these three model.

b) No, it is not plausible that the relationship between y and religion is spurious because the p-values are not much different in these two models.

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