Results Assessment Workbook
Use this workbook after running the HBAT-style case in SmartPLS.
Part 1: Linear Regression Model
Model:
X19 <- X6 + X7 + X9 + X11 + X12
Overall Fit
| Item |
SmartPLS Result |
Interpretation |
| F-test or ANOVA significance |
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| R-square |
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| Adjusted R-square |
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| Durbin-Watson |
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Collinearity
| Predictor |
VIF |
Condition Index Note |
| X6 |
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| X7 |
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| X9 |
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| X11 |
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| X12 |
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Coefficients
| Predictor |
b |
beta |
t |
p |
95% CI |
Interpretation |
| X6 |
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| X7 |
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| X9 |
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| X11 |
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| X12 |
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Assumptions
| Assumption |
SmartPLS Evidence |
Decision |
| Linearity |
Predicted vs residual; predicted vs actual |
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| Homoscedasticity |
Predicted vs residual; Breusch-Pagan |
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| Independence |
Residual autocorrelation; Durbin-Watson |
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| Normality |
QQ plot; residual histogram |
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| Collinearity |
VIF; condition index |
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Part 2: Logistic Regression Model
Model:
X4 <- X6 + X7 + X8 + X9 + X10 + X11 + X12 + X13 + X14 + X15 + X16 + X17 + X18
Fit Summary
| Item |
Null Model |
Estimated Model |
Interpretation |
| Log-likelihood |
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| Deviance |
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| AIC |
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| BIC |
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Pseudo R-Square
| Measure |
Value |
Interpretation |
| McFadden's R-square |
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| Cox and Snell's R-square |
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| Nagelkerke's R-square |
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Classification
| Classification Item |
Value |
Interpretation |
| Correctly classified group 0 |
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| Correctly classified group 1 |
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| Overall classification accuracy |
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Logistic Coefficients
| Predictor |
Coefficient |
Wald |
p |
Odds Ratio |
Interpretation |
| X6 |
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| X7 |
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| X8 |
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| X9 |
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| X10 |
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| X11 |
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| X12 |
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| X13 |
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| X14 |
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| X15 |
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| X16 |
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| X17 |
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| X18 |
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Final Interpretation Prompts
- Which predictors matter most in the linear model?
- Does the linear model explain a meaningful amount of satisfaction variance?
- Which logistic predictors significantly separate region groups?
- Are odds ratios interpreted correctly?
- What limitations should be stated?