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. Author manuscript; available in PMC: 2024 Apr 1.
Published in final edited form as: Psychol Methods. 2021 Sep 27;28(2):401–421. doi: 10.1037/met0000407

Table 2.

Parameter estimates for modeling intervention effects in the Building Blocks data

Parameter Notation Est. SE p
Growth Trajectory Fixed Effects
Intercept γ 000 −2.99 0.07 <.01
Maximum γ 100 1.41 0.12 <.01
Change Offset γ 200 4.78 0.13 <.01
Intervention Fixed Effects
Intercept on Intervention γ 001 0.01 0.07 .86
Maximum on Intervention γ 101 −0.19 0.12 .13
Change Offset on Intervention γ 201 −0.74 0.13 <.01
School-Level Random Effects
Intercept Variance v 00 0.06 0.01 <.01
Maximum Variance v 11 0.11 0.05 .01
Change Offset Variance v 22 0.16 0.06 <.01
Int., Max. Correlation Corr(r00 j, r10 j) 0.89 0.13 <.01
Int., Offset Correlation Corr(r00 j, r20 j) 0.62 0.19 <.01
Max, Offset Correlation Corr(r10 j, r20 j) 0.41 0.27 .15
Person-Level Random Effects
Intercept Variance τ 00 0.41 0.02 <.01
Maximum Variance τ 11 0.81 0.04 <.01
Offset Variance τ 22 0.92 0.09 <.01
Int., Max. Correlation Corr(u0ij, u1ij) 0.75 0.02 <.01
Int., Offset Correlation Corr(u0ij, u2ij) 0.67 0.04 <.01
Max, Offset Correlation Corr(u1ij, u2ij) 0.78 0.03 <.01
Within-Person Residual Variance
Residual Variance σ 2 0.22 0.01 <.01

Note: p-values are obtained from a t-distribution with Donald and Lang (2007) degrees of freedom, which is equal to the number of units at the highest level of the hierarchy (42 schools) minus the number of estimated parameters (19), which is 23.