Below are three regression model that help predict the gross drug cost. Based on the R square, coefficients, t stat, and P-value, what model is the best in predicting the gross drug cost? Why? (For purposes of this assignment, the best models are those that have the smallest prediction errors for future realized drug costs.)

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SUMMARY OUTPUT Regression Statistics Multiple R R Square 0.31644918 0.10014008 Adjusted R Square 0.09996102 Standard Error Observations ANOVA 1366.61069 30160 df SS MS Regression 6 6.3E+09 F 1E+09 559.258 ignificance F 0 Residual Total 30153 5.6E+10 1867625 Intercept RiskScore Gender NLISDummy LISCHOSERDummy SpecialtyDummy 30159 6.3E+10 Coefficients andard Err t Stat -1339.68233 246.221 -5.44097 0.95858323 0.02431 39.4302 -51.9174992 16.4498 -3.15612 -17.0248437 22.2009 -0.76685 93.5768917 24.5595 3.81021 440.395769 16.3267 26.9739 54.6139475 11.3262 4.82192 P-value Lower 95% Upper 95% Lower 95.0% 5.3E-08 -1822.286 -857.0785 -1822.28615 Upper 95.0% -857.0785181 AdjudicationDays 32.414157 76.813738 0 0.9109329 1.0062336 0.9109329 0.0016 -84.15979 -19.67521 -84.1597901 0.44317 -60.5396 26.489913 -60.5396007 0.00014 45.439167 141.71462 45.439167 2E-158 408.39467 472.39686 408.394675 1.4E-06 1.006233564 -19.67520824 26.48991324 141.7146165 472.3968636 76.81373794 Data 5 Data 6 Regression Model 4 Regression Model 5 Regression Model 6 (+) 32.4141571 SUMMARY OUTPUT Regression Statistics Multiple R R Square 0.31644918 0.10014008 Adjusted R Square 0.09996102 Standard Error Observations ANOVA 1366.61069 30160 df SS MS Regression 6 6.3E+09 F 1E+09 559.258 ignificance F 0 Residual Total 30153 5.6E+10 1867625 Intercept RiskScore Gender NLISDummy LISCHOSERDummy SpecialtyDummy 30159 6.3E+10 Coefficients andard Err t Stat -1339.68233 246.221 -5.44097 0.95858323 0.02431 39.4302 -51.9174992 16.4498 -3.15612 -17.0248437 22.2009 -0.76685 93.5768917 24.5595 3.81021 440.395769 16.3267 26.9739 54.6139475 11.3262 4.82192 P-value Lower 95% Upper 95% Lower 95.0% 5.3E-08 -1822.286 -857.0785 -1822.28615 Upper 95.0% -857.0785181 AdjudicationDays 32.414157 76.813738 0 0.9109329 1.0062336 0.9109329 0.0016 -84.15979 -19.67521 -84.1597901 0.44317 -60.5396 26.489913 -60.5396007 0.00014 45.439167 141.71462 45.439167 2E-158 408.39467 472.39686 408.394675 1.4E-06 1.006233564 -19.67520824 26.48991324 141.7146165 472.3968636 76.81373794 Data 5 Data 6 Regression Model 4 Regression Model 5 Regression Model 6 (+) 32.4141571

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To determine the best model for predicting gross drug cost we should consider several criteria including Rsquared coefficient values tstatistics and p... View the full answer