> summary(model4) Call: lm(formula = nh$delta ~ nh$totalpopulation * nh$total * nh$machine + nh$unemploymentrate + nh$percentholdingbachelorsdegree + nh$lat * nh$long) Residuals: Min 1Q Median 3Q Max -0.30281 -0.07168 -0.00144 0.07717 0.40634 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 5.929e+01 1.290e+02 0.459 0.6464 nh$totalpopulation 5.890e-06 7.438e-06 0.792 0.4293 nh$total -4.993e-06 7.575e-05 -0.066 0.9475 nh$machine 8.760e-02 3.521e-02 2.488 0.0136 nh$unemploymentrate -4.817e-04 2.334e-04 -2.064 0.0403 nh$percentholdingbachelorsdegree -4.559e-03 6.477e-04 -7.038 2.74e-11 nh$lat -1.197e+00 2.982e+00 -0.401 0.6886 nh$long 8.176e-01 1.805e+00 0.453 0.6510 nh$totalpopulation:nh$total 7.043e-09 1.727e-08 0.408 0.6838 nh$totalpopulation:nh$machine -9.572e-06 7.865e-06 -1.217 0.2249 nh$total:nh$machine 1.604e-05 7.627e-05 0.210 0.8337 nh$lat:nh$long -1.649e-02 4.171e-02 -0.395 0.6929 nh$totalpopulation:nh$total:nh$machine -6.929e-09 1.727e-08 -0.401 0.6887 (Intercept) nh$totalpopulation nh$total nh$machine * nh$unemploymentrate * nh$percentholdingbachelorsdegree * * * nh$lat nh$long nh$totalpopulation:nh$total nh$totalpopulation:nh$machine nh$total:nh$machine nh$lat:nh$long nh$totalpopulation:nh$total:nh$machine --- Signif. codes: 0 `* * *' 0.001 `* *' 0.01 `*' 0.05 `.' 0.1 ` ' 1 Residual standard error: 0.1159 on 209 degrees of freedom (37 observations deleted due to missingness) Multiple R-Squared: 0.3802, Adjusted R-squared: 0.3446 F-statistic: 10.68 on 12 and 209 DF, p-value: <2.2e-16>anova(model4) > anova(model4) Analysis of Variance Table Response: nh$delta Df Sum Sq Mean Sq F value Pr(>F) nh$totalpopulation 1 0.11603 0.11603 8.6443 0.003650 nh$total 1 0.00695 0.00695 0.5177 0.472632 nh$machine 1 0.36967 0.36967 27.5398 3.769e-07 nh$unemploymentrate 1 0.14791 0.14791 11.0191 0.001064 nh$percentholdingbachelorsdegree 1 0.62402 0.62402 46.4883 9.718e-11 nh$lat 1 0.00133 0.00133 0.0992 0.753048 nh$long 1 0.37698 0.37698 28.0843 2.940e-07 nh$totalpopulation:nh$total 1 0.00209 0.00209 0.1559 0.693390 nh$totalpopulation:nh$machine 1 0.07083 0.07083 5.2769 0.022601 nh$total:nh$machine 1 0.00024 0.00024 0.0182 0.892720 nh$lat:nh$long 1 0.00241 0.00241 0.1795 0.672213 nh$totalpopulation:nh$total:nh$machine 1 0.00216 0.00216 0.1610 0.688670 Residuals 209 2.80545 0.01342 nh$totalpopulation * * nh$total nh$machine * * * nh$unemploymentrate * * nh$percentholdingbachelorsdegree * * * nh$lat nh$long * * * nh$totalpopulation:nh$total nh$totalpopulation:nh$machine * nh$total:nh$machine nh$lat:nh$long nh$totalpopulation:nh$total:nh$machine Residuals --- Signif. codes: 0 `***' 0.001 `**' 0.01 `*' 0.05 `.' 0.1 ` ' 1
Race may not be a huge factor in NH because my anecdotal impression (I've never been there) is that it's pretty darn overwhelmingly white.
That won't necessarily show up on census data, will it? Though it is worth getting the data just in case a 1% shift in the gender ratio from town to town actually explains something. We have met the enemy, and he is us — Pogo
Can you do a correlation matrix of the predictor variables? We have met the enemy, and he is us — Pogo
