Table 4. Fit indices and parameter estimates from the limited information multilevel latent growth models.
Coefficient 
Betweenlevel 
Withinlevel 
Fit Indices 
Effect 
t value 
Effect 
t value 
Intrinsic Motivation 
Means 
Intercept 

 2.21 
25.04 
χ^{2} = 86.05 df = 17 
Slope 

 .07 
.49 
p < .01 
Quadratic 

 .04 
.52 
NFI = .920 
Cubic 

 .01 
.56 
CFI = .926 
Variances 
RMSEA = .146 
Intercept 
.14 
.78 
.16 
2.67 
90% CI = 
Slope 
.12 
.35 
.42 
3.43 
(.118, .174) 
Quadratic 
.02 
.32 
.09 
4.02 

Cubic 
.00 
.23 
.01 
4.11 

Identified Regulation 
Means 
Intercept 

 .68 
7.36 
χ^{2} = 35.23 df = 17 
Slope 

 1.85 
13.48 
p < .01 
Quadratic 

 .66 
9.97 
NFI = .984 
Cubic 

 .07 
8.18 
CFI = .992 
Variances 
RMSEA = .049 
Intercept 
.16 
.71 
.15 
2.27 
90% CI = 
Slope 
.06 
.16 
.08 
.68 
(.010, .083) 
Quadratic 
.00 
.00 
.01 
.52 

Cubic 
.00 
.02 
.00 
.03 

Introjected Regulation 
Means 
Intercept 

 2.33 
24.98 
χ^{2} = 59.33 df = 17 
Slope 

 .19 
1.76 
p < .01 
Quadratic 

 .14 
2.67 
NFI = .968 
Cubic 

  .03 
3.65 
CFI = .973 
Variances 
RMSEA = .108 
Intercept 
.15 
.79 
.48 
7.01 
90% CI = 
Slope 
.00 
.00 
.29 
2.81 
(.080, .137) 
Quadratic 
.01 
.14 
.02 
.95 

Cubic 
.00 
.24 
.00 
.06 

External Regulation 
Means 
Intercept 

 1.83 
19.06 
χ^{2} = 51.47 df = 17 
Slope 

 .10 
.83 
p < .01 
Quadratic 

 .02 
.40 
NFI = .973 
Cubic 

 .00 
.33 
CFI = .977 
Variances 
RMSEA = .107 
Intercept 
.16 
.96 
.26 
4.34 
90% CI = 
Slope 
.16 
.60 
.00 
.00 
(.080, .137) 
Quadratic 
.03 
.52 
.02 
.99 

Cubic 
.00 
.00 
.01 
1.01 

Amotivation 
Means 
Intercept 

 .60 
6.82 
χ^{2} = 67.07 df = 26 
Slope 

 .51 
7.44 
p < .01 
Quadratic 

 .73 
53.05 
NFI = .960 
Variances 
CFI = .971 
Intercept 
.11 
1.02 
.43 
11.67 
RMSEA = .079 
Slope 
.06 
1.00 
.12 
6.26 
90% CI = 
Quadratic 
.01 
1.00 
.09 
4.52 
(.059, .101) 