# Regression Outputs

See Regression for a description of how to generate the outputs described on this page and Regression Troubleshooting for a description of some common difficulties and their solutions.

## p-Values by question

The first table of the output screen contains p-values for significance tests for all of the Independent questions. The word `INCLUDED` indicates the question is in the final model. `EXCLUDED` will appear if the question has been excluded by stepwise selection.

p-values of All Questions (Included and Excluded) p-Values INCLUDED Satisfaction with fees (linear) .000 INCLUDED Satisfaction with interest rates (linear) .000 INCLUDED Satisfaction with phone (linear) .000 INCLUDED Satisfaction with branch (linear) .000 INCLUDED Satisfaction with availability of ATMs (linear) .000 INCLUDED Satisfaction with online (categorical) .000

## Goodness of fit statistics

The R-Squared and Adjusted R-Squared are computed in the traditional way for linear regression models. For the other models, McFadden’s Rho-squared is employed. The AIC, which appears for all the models except linear regression, can be used for comparing different models (all else being equal, a lower AIC indicates a better model).

Dependent question: Overall satisfaction (Linear) Standard error of the residuals (model): .14557 R-Squared: .458 Adjusted R-Squared: .453 Model p-value: .00000

The following table of coefficients is interpreted in the standard way (see any book on regression or an econometrics textbook; some are listed below).

Coef S.E. t-Stat p-Value Beta VIF Constant (intercept) -.288 .034 -8.489 .000 NaN NaN fees (linear) .353 .027 13.120 .000 .327 1.008 interest rates (linear) .303 .026 11.729 .000 .292 1.003 phone (linear) .315 .028 11.256 .000 .281 1.011 branch (linear) .128 .010 13.087 .000 .326 1.008 availability of ATMs (linear) .214 .025 8.420 .000 .211 1.018 online (categorical) Very dissatisfied + 2 .000 NaN NaN NaN NaN NaN 3 .036 .017 2.191 .029 .086 2.495 4 .082 .016 5.046 .000 .201 2.586 5 + Very satisfied .120 .018 6.669 .000 .242 2.140

See Ordered Logit and Multinomial Logistic Discriminant Analysis for additional information on the interpretation of outputs from these models.

## Good textbooks describing the interpretation of regression models

### Introductory

Fox, John (1997), Applied Regression Analysis, Linear Models, and Related Methods. Thousand Oaks: SAGE Publications

Kennedy, Peter (2008), A Guide to Econometric: Blackwell, 6th Edition

### Advanced

Greene, William H. (1997), Econometric Analysis (International ed.). Upper Saddle River, New Jersey: Prentice-Hall International

Cameron, A. Colin and Pravin K. Trivedi. (2005), Microeconometrics: Methods and Applications. Cambridge: Cambridge University Press.