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. Author manuscript; available in PMC: 2010 Apr 22.
Published in final edited form as: J Sch Psychol. 2006 Feb 1;44(1):31–49. doi: 10.1016/j.jsp.2005.12.001

Table 2.

Hierarchical logistic regression analyses predicting retention from child and school variables

Modela bb s(b) χ2 (1) Sig. R2 total (df)c Sig. Δχ2 (df)
Academic competence 0.275 (5)
 Unit IQ 0.008 0.014 0.957
 Reading W −0.044 0.010 0.000
 Math W 0.012 0.013 0.324
 Teacher-rated engagement −0.139 0.203 0.496
 Teacher-rated achievement −0.064 0.203 0.713
Socio-demographic characteristics 0.331 (8) 0.008 (3)
 Economic disadvantage 0.317 0.472 0.502
 Gender −0.227 0.358 0.527
 Age −1.514 0.522 0.004
Personality resiliency 0.227 (7) 0.766 (2)
 Effortful control −0.356 0.229 0.120
 Ego resiliency −0.138 0.288 0.633
Social, emotional, and behavioral 0.287 (9) 0.630 (4)
 Aggression −0.251 0.200 0.210
 Hyperactivity −0.087 0.190 0.646
 Emotional problems 0.029 0.229 0.900
 Peer acceptance −0.071 0.232 0.760
School context 0.280 (9) 0.890 (4)
 Bilingual classroom 0.214 0.514 0.678
 % Hispanic students in classroom 0.001 0.007 0.893
 Teacher-rated support −0.111 0.295 0.707
 Teacher-rated conflict 0.005 0.225 0.981

N =283 for all regressions.

a

Model 1 involves only variables in the Academic Competence block. Each of the other blocks was added hierarchically and sequentially to the Academic Competence block. Thus, all models except the Academic Competence model involved two blocks, with Academic Competence always the first block.

b

For Model 1, the betas are based on simultaneous entry of all variables in Block 1. For all other models, the betas are for the individual variable added hierarchically to the Academic Competence block.

c

The first R2 is after variables in the Academic Competence block are entered; subsequent R2’s are the contribution of both Block 1 and the block associated with it.