Model fit statistics
| M1 | M2 | M3 | M4 | |
|---|---|---|---|---|
| Metric | Product and process development | Commercialisation of academic invention | Access to student talent | Efficiency increase of business operations |
| −2 Log Likelihood | 2575.53 | 2114.91 | 2502.08 | 2570.84 |
| AIC (smaller is better) | 2627.53 | 2164.91 | 2552.08 | 2620.84 |
| AICC (smaller is better) | 2627.91 | 2165.28 | 2552.44 | 2621.2 |
| BIC (smaller is better) | 2604.09 | 2142.37 | 2529.55 | 2598.31 |
| CAIC (smaller is better) | 2630.09 | 2167.37 | 2554.55 | 2623.31 |
| HQIC (smaller is better) | 2580.42 | 2119.61 | 2506.79 | 2575.54 |
| Fit statistics for conditional distribution | ||||
| −2 log L (Contribution the target| r. effects) | 2570.09 | 2114.91 | 2502.08 | 2570.84 |
| Pearson Chi-Square | 3135.29 | 3269.32 | 3187.44 | 3053.13 |
| Pearson Chi-Square/DF | 0.85 | 0.93 | 0.86 | 0.83 |
| M1 | M2 | M3 | M4 | |
|---|---|---|---|---|
| Metric | Product and process development | Commercialisation of academic invention | Access to student talent | Efficiency increase of business operations |
| −2 Log Likelihood | 2575.53 | 2114.91 | 2502.08 | 2570.84 |
| AIC (smaller is better) | 2627.53 | 2164.91 | 2552.08 | 2620.84 |
| AICC (smaller is better) | 2627.91 | 2165.28 | 2552.44 | 2621.2 |
| BIC (smaller is better) | 2604.09 | 2142.37 | 2529.55 | 2598.31 |
| CAIC (smaller is better) | 2630.09 | 2167.37 | 2554.55 | 2623.31 |
| HQIC (smaller is better) | 2580.42 | 2119.61 | 2506.79 | 2575.54 |
| −2 log L (Contribution the target| r. effects) | 2570.09 | 2114.91 | 2502.08 | 2570.84 |
| Pearson Chi-Square | 3135.29 | 3269.32 | 3187.44 | 3053.13 |
| Pearson Chi-Square/DF | 0.85 | 0.93 | 0.86 | 0.83 |
Note(s): Across the four specifications, Model 2 (Invention) provides the best empirical fit: it attains the lowest −2 log likelihood and the smallest values on AIC, AICC, BIC, CAIC and HQIC, indicating the most favourable balance of fit and parsimony. All models show Pearson χ2/DF between 0.83 and 0.93, which implies only mild under dispersion rather than gross misfit. Overall, the four models capture meaningful structure in the data (information criteria and likelihood improve markedly from some alternatives to Model 2), but none exhibits signs of severe lack of fit; substantive inference should proceed after inspection of coefficients and standard diagnostics
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