Table 4.
Effect on study outcome: Model comparisons
Mo-del | predictor | ß | SE | 95% CI | p | AIC | BIC | χ² (∆ df) | ∆ p | ||
---|---|---|---|---|---|---|---|---|---|---|---|
1 | - | - | - | - | - | 3011.2 | 3026.2 | ||||
2 | GPA | 0.321 | 0.029 | 0.263 | 0.378 | *** | 2898.4 | 2918.3 | |||
Model 1 vs. Model 2 | 114.842( 1 ) | *** | |||||||||
3 | TMS | 0.251 | 0.041 | 0.172 | 0.331 | *** | 2863.4 | 2888.2 | |||
Model 2 vs. Model 3 | 37.049( 1 ) | *** | |||||||||
4 | VT | 0.325 | 0.125 | 0.081 | 0.570 | ** | 2858.6 | 2888.4 | |||
Model 3 vs. Model 4 | 6.762( 1 ) | ** | |||||||||
5 | Age | 0.001 | 0.034 | -0.066 | 0.068 | 0.977 | 2860.6 | 2895.4 | |||
Model 4 vs. Model 5 | 0.000( 1) | 0.985 | |||||||||
6 | Sex | -0.214 | 0.059 | -0.330 | -0.098 | *** | 2847.6 | 2882.4 | |||
Model 4 vs. Model 6 | 12.998 (1) | *** | |||||||||
7 | VT*Age | 0.090 | 0.089 | -0.084 | 0.264 | 0.310 | 2877.2 | 2921.8 | |||
Model 6 vs. Model 7 | 0.855 (2) | 0.652 |
Note. Random-Intercept Models with predictors as fixed effects, DV = study outcome parameter; N = 1063; GPA = German “Abitur”; VT = completed relevant vocational training; Model 1 = Medical school as varying intercept; Model 2 = Model 1 + GPA as fixed effect; Model 3 = Model 2 + TMS as fixed effect; Model 4 = Model 3 + VT as fixed effect; Model 5 = Model 4 + Age as fixed effect; Model 6 = Model 4 + Sex as fixed effect; Model 7 = Model 6 + Age*VT interaction as fixed effect; AIC = Akaike’s Information Criterion; BIC = Schwarz’s Bayesian Criterion; ∆ p = Significance of model difference; * p < .05, ** p < .01 *** p < .001