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. 2022 Jul 6;27(4):933–948. doi: 10.1007/s10459-022-10120-y

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