sociology Unit B1: Introduction to correlation and regression 3/3 Brendan Halpin May

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1 Unit B1: Introduction to correlation and regression 3/3 Brendan Halpin Department of Sociology, University of Limerick May

2 Multicollinearity Topics 1 Multicollinearity 2 Leverage 3 Residuals

3 Multicollinearity 3 Multicollinearity 1. use (Body Fat). corr * (obs=20) triceps thigh midarm bodyfat triceps thigh midarm bodyfat

4 Multicollinearity 4 Multicollinearity 2. reg bodyfat tricep Source SS df MS Number of obs = 20 F(1, 18) = Model Prob > F = Residual R-squared = Adj R-squared = Total Root MSE = bodyfat Coef. Std. Err. t P> t [95% Conf. Interval] triceps _cons

5 Multicollinearity 5 Multicollinearity 3. reg bodyfat thigh Source SS df MS Number of obs = 20 F(1, 18) = Model Prob > F = Residual R-squared = Adj R-squared = Total Root MSE = bodyfat Coef. Std. Err. t P> t [95% Conf. Interval] thigh _cons

6 Multicollinearity 6 Multicollinearity 4. reg bodyfat midarm Source SS df MS Number of obs = 20 F(1, 18) = 0.37 Model Prob > F = Residual R-squared = Adj R-squared = Total Root MSE = bodyfat Coef. Std. Err. t P> t [95% Conf. Interval] midarm _cons

7 Multicollinearity 7 Multicollinearity 5. reg bodyfat tricep thigh midarm Source SS df MS Number of obs = 20 F(3, 16) = Model Prob > F = Residual R-squared = Adj R-squared = Total Root MSE = 2.48 bodyfat Coef. Std. Err. t P> t [95% Conf. Interval] triceps thigh midarm _cons

8 Multicollinearity 8 Multicollinearity 6. estat vif Variable VIF 1/VIF triceps thigh midarm Mean VIF

9 Leverage Topics 1 Multicollinearity 2 Leverage 3 Residuals

10 Leverage 10 Leverage 1. sysuse auto (1978 Automobile Data). reg price weight mpg Source SS df MS Number of obs = 74 F(2, 71) = Model Prob > F = Residual R-squared = Adj R-squared = Total Root MSE = 2514 price Coef. Std. Err. t P> t [95% Conf. Interval] weight mpg _cons

11 Leverage 11 Leverage 2. dfbeta. predict cd, cooks. su _df* cd _dfbeta_1: dfbeta(weight) _dfbeta_2: dfbeta(mpg) Variable Obs Mean Std. Dev. Min Max _dfbeta_ _dfbeta_ cd e list make cd _df* if _dfbeta_1>1 make cd _dfbet ~ 1 _dfbet ~ Cad. Seville

12 Leverage 12 Leverage 3

13 Residuals Topics 1 Multicollinearity 2 Leverage 3 Residuals

14 Residuals 14 Residuals. sysuse auto (1978 Automobile Data). reg price weight mpg Source SS df MS Number of obs = 74 F(2, 71) = Model Prob > F = Residual R-squared = Adj R-squared = Total Root MSE = 2514 price Coef. Std. Err. t P> t [95% Conf. Interval] weight mpg _cons predict res, res. scatter res weight

15 Residuals 15 Residuals

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