Table 2.
Model 1. Results of the binary logistic regression
| Variables | B | S.E | Wald | df | Sig | Exp(B) |
|---|---|---|---|---|---|---|
| Gendera | .244 | .118 | 4.3 | 1 | .038 | 1.277 |
| Citizenshipb | .363 | .32 | 1.285 | 1 | .257 | 1.438 |
| Passive semestersc | -2.245 | .69 | 10.59 | 1 | .001 | .106 |
| The pace of credit accumulationd | 3.786 | .231 | 268.054 | 1 | < 0.001 | 44.099 |
| Form of financee | 1.771 | .319 | 30.862 | 1 | < 0.001 | 5.879 |
| Constant | -2.205 | .125 | 312.039 | 1 | < 0.001 | .110 |
Source: Higher Education Information System Hungary, Hungarian Educational Authority, own edition
a0 – Female, 1 – male.
b0-Hungarian, 1- Foreign
c0-Less than 2,1-2 or more
dWe coded the pace of credit accumulation by the number of credits gained by the student at the end of the fourth semester: 0 – The student gained at least 60% of the suggested number of credits specified by the institution (120 credits), 1 – The student gained less than 60% of the suggested number of credits.
e0- State-financed,1 -Self-financed