Page 185 - Second language development of newly arrived migrant kindergarteners - Frederike Groothoff

The influence of the school learning environment 185 the new growth models, we will present the significant explanatory variables from the school learning environment first, followed by the discussion of the non-significant variables. Number of Different Words (NDW) From the comparison between the models for NDW (Table 8.9) it is apparent that a model with a fixed linear component – allowing for differences in Age – fit the data better than a model with only an intercept (ΔΧ2 (NDWII) = 71.72; df = 1; p < .001). The variance within, or between individuals depends on Age (NDWIII and NDWIV). Adding Age2 to the model did not improve the fit significantly (NDWV). Hence, in the final model (NDWII) a fixed effect of Age is needed, and with this model we continued the analysis. Table 8.9: Fit of Different Polynomials (-2LL) for Changes in NDW (162 cases) as well as the Comparison of Consecutive Models. Comparison -2LL Models ΔΧ2 Δdf p <.001 .88ns .13ns .18ns Model NDWI: β0ijcons a 1314.56 NDWII: NDWI + β1Age1ij NDWII: NDWII + e1ijAge1ij NDWIV: NDWIII + u10jAge1i NDWV: NDWIV + β2Age2ij 1242.85 NDWI vs NDWII 1242.59 NDWII vs NDWIII 1238.56 NDWIII vs NDWIV 1236.74 NDWIV vs NDWV 71.72 1 0.26 2 4.03 2 1.82 1 a In addition to the intercept, variance components for differences within and between individuals are estimated. Based on this General Development Model we constructed Figure 8.7, in which both the average development of NDW as well as the differences within and between individuals are represented (see Table 6.7 in Appendix 6 for the parameter estimates). The average NDW score at an age of 73 months was estimated as 35.56. Each month a child grew older, his NDW score increased by 0.71.