Table 4 Multilevel mixed-effects logistic regression models (random slope models) of the enrolment decision of students to a master programme.
Model I | Model II | |||
|---|---|---|---|---|
\(\beta\) | \(\exp ({\beta}^{\rm{a}})\) | \(\beta\) | \(\exp (\beta )\) | |
Gender (women) | ||||
Men | −0.02 | 0.98 | 0.05 | 1.05 |
Age | −0.07 | 0.93 | −0.07 | 0.93 |
Residence area (urban) | ||||
Rural | −0.36 | 0.69 | −0.374 | 0.69 |
Grade | 0.24*** | 1.27 | 0.294** | 1.34 |
Father education (low) | ||||
Medium | 1.14 | 1.15 | 0.21 | 1.23 |
High | 0.64* | 1.89 | 0.73* | 2.07 |
Subjective income (easy) | ||||
With difficulty | 0.18 | 1.20 | 1.20 | 1.22 |
Working contract type (not working) | ||||
Full-time | 0.97*** | 2.63 | 1.03 | 2.80 |
Part-time | 0.34 | 1.40 | 0.37 | 1.44 |
Seniority | −0.21*** | 0.80 | −0.227** | 0.80 |
Perceived master degree graduates wage | 0.00006 | 1.00 | 0.00007 | 1.00 |
Perceived master degree unemployed | −0.00008 | 0.99 | −0.0009 | 0.99 |
Field of study (STEM) | ||||
Non-STEM | −0.835* | 2.30 | −0.79** | 0.45 |
University score | 0.02* | 1.07 | 0.032* | 1.03 |
Enterprises introducing product innovations | −0.79*** | 0.45 | ||
STEM * Enterprises introducing product innovations | 1.06** | 2.90 | ||
Constant | 0.85 | 1.51 | 4.53 | |
Observations | 476 | 476 | ||
No. of groups | 5 | 5 | ||
Log-likelihood | −301.72 | −298.39 | ||
(Intercept variance)\({{\boldsymbol{\sigma }}}_{{\boldsymbol{uo}}}^{{\boldsymbol{2}}}\) | 0.062 | 0.09 | ||
Slope variance \({{\boldsymbol{\sigma }}}_{{\boldsymbol{u}}{\boldsymbol{1}}}^{{\boldsymbol{2}}}\) | 1.29 | 0.46 | ||
Intercept-slope covarianceb \({{\boldsymbol{\sigma }}}_{{\boldsymbol{u}}{\boldsymbol{01}}}\) | −0.215 | −0.198 | ||
Variance at regional levelc (%) | 1.85% | 2.7% | ||
Lr test | 10.51*** | 5.42*** | ||
