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Table 3 Multilevel logistic regression on higher education

From: Social origin and educational attainment in China: a historical analysis of 70 birth cohorts

  Model 1 Model 2 Model 3
Coef. (std.error) Coef. (std.error) Coef. (std.error)
Intercept (γ00) − 2.0297(.1109)*** − 2.7717(.1273)*** − 2.7697(.1282)***
Male (γ10)   .4324 (.0344)*** .5438 (.0489)***
Urban (γ20)   .5720 (.0366)*** .4813 (.0528)***
Fmedu (γ30)   .1557 (.0052)*** .1506 (.0067)***
Fmisei (γ40)   .0354 (.0015)*** .0372 (.0019)***
  Variance component Variance component Variance component
Intercept (σ2u0) .8037*** 1.0180*** 1.0270***
Male (σ2u1)    7.108e−02***
Urban (σ2u2)    8.291e−02***
fmedu (σ2u3)    1.130e−03***
fmisei (σ2u4)    3.518e−05***
Error variance (σ2ε) 0.8655 .7856 0.7808
AIC 2787.6 22872.2 22751.1
BIC 27887.5 2293.0 22920.5
− log likelihood 13933.3 1143.0 11355.5
Individual observation 35400 35400 35400
Group observation 70 70 70
  1. AIC Akaike information criterion, BIC Bayesian information criterion
  2. ***p < 0.001