PROBLEM 1 Call: lm(formula = fla$bush04 ~ fla$etouch) Residuals: Min 1Q Median 3Q Max -0.311761 -0.054553 -0.004049 0.077816 0.181817 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 0.60975 0.01441 42.327 <2e-16 *** fla$etouch -0.06502 0.03045 -2.136 0.0365 * --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Residual standard error: 0.1039 on 65 degrees of freedom Multiple R-squared: 0.06556, Adjusted R-squared: 0.05118 F-statistic: 4.56 on 1 and 65 DF, p-value: 0.03649 Covariate Balance on the 13 covariates (income ....foreign born) [,1] [,2] [,3] [1,] 3.928160e+04 3.426065e+04 0.83286152 [2,] 4.558346e-01 4.250467e-01 0.40343743 [3,] 4.392972e-01 4.461641e-01 -0.08672082 [4,] 4.632819e-01 4.153981e-01 0.53486639 [5,] 5.134214e-01 5.591344e-01 -0.50683992 [6,] 3.878838e-01 6.041861e-01 -1.19775217 [7,] 4.347231e-01 2.866394e-01 1.10469367 [8,] 7.133490e-01 6.707677e-01 0.72759818 [9,] 1.219124e-01 7.477541e-02 0.47874139 [10,] 8.683429e-01 8.203834e-01 0.49275633 [11,] 1.076757e-01 1.517273e-01 -0.45051174 [12,] 4.497937e-02 5.508301e-02 -0.37639896 [13,] 1.314320e-01 5.864216e-02 1.02275191 Call: lm(formula = fla$bush04 ~ fla$etouch + fla$votePer96.rep + fla$votePer00.rep + fla$regPer00.rep + fla$turnout00) Residuals: Min 1Q Median 3Q Max -0.0546952 -0.0088137 0.0008637 0.0132179 0.0550585 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) -0.022445 0.039375 -0.570 0.570757 fla$etouch -0.002893 0.007751 -0.373 0.710258 fla$votePer96.rep -0.341049 0.094730 -3.600 0.000639 *** fla$votePer00.rep 1.374532 0.073116 18.799 < 2e-16 *** fla$regPer00.rep -0.020294 0.029614 -0.685 0.495748 fla$turnout00 0.032243 0.051335 0.628 0.532287 --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Residual standard error: 0.02272 on 61 degrees of freedom Multiple R-squared: 0.9581, Adjusted R-squared: 0.9546 F-statistic: 278.8 on 5 and 61 DF, p-value: < 2.2e-16 Call: lm(formula = fla$bush04 ~ fla$etouch + fla$votePer96.rep + fla$votePer00.rep + fla$hisp00 + fla$white00 + fla$black00) Residuals: Min 1Q Median 3Q Max -0.0389045 -0.0117206 -0.0006346 0.0100186 0.0651239 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 0.119433 0.229772 0.520 0.6051 fla$etouch -0.007879 0.006997 -1.126 0.2646 fla$votePer96.rep -0.375278 0.065986 -5.687 4.06e-07 *** fla$votePer00.rep 1.334309 0.058899 22.654 < 2e-16 *** fla$hisp00 -0.058290 0.026725 -2.181 0.0331 * fla$white00 -0.071099 0.234583 -0.303 0.7629 fla$black00 -0.168842 0.233614 -0.723 0.4726 --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Residual standard error: 0.02061 on 60 degrees of freedom Multiple R-squared: 0.966, Adjusted R-squared: 0.9627 F-statistic: 284.5 on 6 and 60 DF, p-value: < 2.2e-16 Call: lm(formula = fla$bush04 ~ fla$etouch + fla$votePer96.rep + fla$votePer00.rep + fla$hisp00 + fla$black00 + fla$lowEduc00 + fla$foreignBorn00) Residuals: Min 1Q Median 3Q Max -0.0433338 -0.0126145 -0.0000533 0.0113269 0.0663672 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 0.057369 0.022577 2.541 0.013703 * fla$etouch -0.005979 0.007373 -0.811 0.420681 fla$votePer96.rep -0.310844 0.082055 -3.788 0.000358 *** fla$votePer00.rep 1.265667 0.079448 15.931 < 2e-16 *** fla$hisp00 -0.030876 0.083642 -0.369 0.713343 fla$black00 -0.113770 0.032200 -3.533 0.000805 *** fla$lowEduc00 0.134398 0.171208 0.785 0.435595 fla$foreignBorn00 -0.075752 0.104195 -0.727 0.470087 --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Residual standard error: 0.02054 on 59 degrees of freedom Multiple R-squared: 0.9668, Adjusted R-squared: 0.9629 F-statistic: 245.7 on 7 and 59 DF, p-value: < 2.2e-16 PROBLEM 2 Matches on a single variable [,1] [,2] [,3] [1,] 6 1 1.662279e-02 [2,] 8 59 3.080718e-04 [3,] 11 10 9.106891e-03 [4,] 28 3 2.291353e-03 [5,] 30 57 1.487119e-02 [6,] 34 55 8.643568e-03 [7,] 35 40 2.029964e-02 [8,] 42 46 2.684682e-03 [9,] 43 64 3.768249e-03 [10,] 45 48 4.066537e-03 [11,] 50 66 3.639661e-05 [12,] 51 9 5.014988e-04 [13,] 52 41 5.298470e-03 [14,] 56 44 3.347064e-03 [15,] 60 53 1.118887e-02 Covariate balance for matched pairs (note improvement on variable 10 ... the matching variable) [,1] [,2] [,3] [1,] 3.928160e+04 3.965107e+04 -0.06251070 [2,] 4.558346e-01 3.934062e-01 0.70194877 [3,] 4.392972e-01 4.916074e-01 -0.56555419 [4,] 4.632819e-01 3.980242e-01 0.63299928 [5,] 5.134214e-01 5.750912e-01 -0.58628747 [6,] 3.878838e-01 3.989121e-01 -0.13612296 [7,] 4.347231e-01 4.329299e-01 0.02235185 [8,] 7.133490e-01 6.834994e-01 0.99683547 [9,] 1.219124e-01 6.921080e-02 0.51271517 [10,] 8.683429e-01 8.690836e-01 -0.01195969 [11,] 1.076757e-01 9.616483e-02 0.20758046 [12,] 4.497937e-02 3.409660e-02 0.78183530 [13,] 1.314320e-01 6.790388e-02 0.71830308 Estimated treatment effect and standard error [1] -0.07070295 0.03369587 15 [1] -0.07936747 0.04320114 11 (dist < .01) [1] -0.07368910 0.06034505 8 (dist < .005) Matches using Mahalnobis distance on all variables [,1] [,2] [,3] [1,] 6 17 22.607154 [2,] 8 9 3.617787 [3,] 11 40 19.816804 [4,] 28 48 11.347031 [5,] 30 58 5.245561 [6,] 34 53 3.724937 [7,] 35 41 7.023151 [8,] 42 5 11.010461 [9,] 43 27 51.723931 [10,] 45 55 9.769571 [11,] 50 64 14.042120 [12,] 51 26 4.957831 [13,] 52 54 11.171726 [14,] 56 3 13.398922 [15,] 60 66 10.582341 Covariate balance for matched pairs (considerably better than above except for last variable) [,1] [,2] [,3] [1,] 3.928160e+04 3.667947e+04 0.4672167 [2,] 4.558346e-01 4.272532e-01 0.3840429 [3,] 4.392972e-01 4.527346e-01 -0.1850475 [4,] 4.632819e-01 4.352112e-01 0.3233564 [5,] 5.134214e-01 5.390355e-01 -0.2957324 [6,] 3.878838e-01 4.242036e-01 -0.4457632 [7,] 4.347231e-01 4.148317e-01 0.2731690 [8,] 7.133490e-01 6.998453e-01 0.3426674 [9,] 1.219124e-01 6.474424e-02 0.5645769 [10,] 8.683429e-01 8.785880e-01 -0.1714709 [11,] 1.076757e-01 9.482903e-02 0.2368995 [12,] 4.497937e-02 4.006733e-02 0.3313181 [13,] 1.314320e-01 6.761960e-02 0.7307638 Estimated treatment effect and standard error [1] -0.04083823 0.02472602 15 [1] -0.03254117 0.02502002 14 (dist < 25) [1] -0.00411685 0.01797000 10 (dist < 12)