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Table 4 Measurement invariance across genders (N = 1387) and educational levels (N = 1398)

From: Homework self-regulation strategies: a gender and educational-level invariance analysis

Model χ 2 df p χ 2/df CFI RMSEA 90% CI RMSEA SRMR BIC ΔSB − χ 2 (df) ΔCFI ΔRMSEA
Gender
 Model 0: configural 1378.467 372 <.001 3.706 .903 .062 .059–.066 .059 80267.581
 Model 1: metric 1408.690 393 <.001 3.584 .902 .061 .058–.065 .063 80141.507 24.302 (21) .001 .001
 Model 2: scalar 1545.190 414 <.001 3.732 .891 .063 .059–.066 .077 80138.773 147.374 (21)*** .011 .002
 Model 3a: partial scalar 1528.940 413 <.001 3.702 .892 .062 .059–.066 .077 80127.547 128.712 (20)*** .010 .001
Educational level
 Model 0: configural 1392.982 372 <.001 3.745 .904 .063 .059–.066 .059 80759.100    
 Model 1: metric 1451.976 393 <.001 3.695 .901 .062 .059–.066 .068 80666.025 56.208 (21)*** .003 .001
 Model 2: scalar 1749.108 414 <.001 4.225 .875 .068 .065–.071 .080 80851.854 339.662 (21)*** .026 .006
 Model 3b: partial scalar 1537.974 410 <.001 3.751 .894 .063 .059–.066 .071 80632.473 90.717 (17)*** .007 .001
  1. CFI comparative fit index, RMSEA root mean square error of approximation, SRMR standardized root mean square residual, BIC Bayesian information criterion, ΔSB − χ 2 Satorra–Bentler scaled chi-square difference test
  2. ***p < .001
  3. aEstimating freely the intercept of item 14 in both samples
  4. bEstimating freely the intercepts of items 12, 14, 16 and 18 in both samples