Table 2.
Monte Carlo Estimates (Mean Only) at Some Specific Conditions
| Standard estimation | Mixture estimation | |||||
|---|---|---|---|---|---|---|
|
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| Group | Growth factor | Parameter | Generated | Generated | Missing | Same |
| Condition 1: Quadratic slope added
| ||||||
| G1 | Intercept | 5.0 | 5.001 (.081) | 5.001 (.081) | 5.004 (.081) | 5.005 (.081) |
| Linear slope | 0.1 | 0.089 (.072) | 0.089 (.072) | 0.089 (.072) | 0.089 (.072) | |
| Quad slope | 0.02 | 0.022 (.019) | 0.022 (.019) | 0.022 (.019) | 0.022 (.019) | |
|
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| G2 | Intercept | 3.0 | 2.974 (.144) | 2.974 (.144) | 2.974 (.144) | 2.974 (.144) |
| Linear slope | 0.5 | 0.530 (.130) | 0.530 (.130) | 0.530 (.130) | 0.530 (.130) | |
| Quad slope | 0.03 | 0.022 (.033) | 0.022 (.033) | 0.022 (.033) | 0.022 (.033) | |
|
| ||||||
| G3 | Intercept | 7.0 | 6.997 (.204) | 6.997 (.204) | 6.997 (.204) | 7.000 (.204) |
| Linear slope | −0.1 | −0.115 (.183) | −0.115 (.183) | −0.116 (.183) | −0.115 (.183) | |
| Quad slope | 0.04 | 0.045 (.047) | 0.045 (.047) | 0.045 (.047) | 0.045 (.047) | |
|
| ||||||
| G4 | Intercept | 6.0 | 5.987 (.278) | 5.987 (.278) | 5.989 (.284) | 6.000 (.268) |
| Linear slope | −0.6 | −0.624 (.257) | −0.624 (.257) | −0.620 (.347) | −0.674 (.286) | |
| Quad slope | 0.02 | 0.020 (.067) | 0.020 (.067) | 0.017 (.114) | 0.020 (.069) | |
|
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| Condition 2: Continuous covariate added
| ||||||
| G1 | Intercept | 5.0 | 4.986 (.073) | 4.986 (.073) | 4.986 (.073) | 4.986 (.073) |
| Linear lope | 0.1 | 0.100 (.024) | 0.100 (.024) | 0.100 (.024) | 0.100 (.025) | |
|
| ||||||
| G2 | Intercept | 3.0 | 2.997 (.131) | 2.997 (.131) | 2.997 (.131) | 2.997 (.131) |
| Linear lope | 0.5 | 0.496 (.043) | 0.496 (.043) | 0.496 (.043) | 0.496 (.043) | |
|
| ||||||
| G3 | Intercept | 7.0 | 7.000 (.185) | 7.000 (.185) | 7.000 (.185) | 6.999 (.186) |
| Linear lope | −0.1 | −0.101 (.060) | −0.101 (.060) | −0.101 (.060) | −0.102 (.061) | |
|
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| G4 | Intercept | 6.0 | 5.995 (.259) | 5.995 (.259) | 6.010 (.265) | 5.991 (.300) |
| Linear lope | −0.6 | −0.592 (.086) | −0.592 (.086) | −0.607 (.109) | −0.590 (.131) | |
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| Condition 3: Increased missing proportion (50%)
| ||||||
| G1 | Intercept | 5.0 | 5.003 (.085) | 5.003 (.085) | 5.003 (.085) | 5.003 (.085) |
| Linear lope | 0.1 | 0.097 (.031) | 0.097 (.031) | 0.097 (.031) | 0.097 (.031) | |
|
| ||||||
| G2 | Intercept | 3.0 | 3.000 (.151) | 3.000 (.151) | 3.000 (.151) | 3.000 (.151) |
| Linear lope | 0.5 | 0.500 (.054) | 0.500 (.054) | 0.500 (.055) | 0.500 (.055) | |
|
| ||||||
| G3 | Intercept | 7.0 | 6.981 (.212) | 6.981 (.212) | 6.981 (.213) | 6.981 (.213) |
| Linear lope | −0.1 | −0.104 (.078) | −0.104 (.078) | −0.104 (.078) | −0.104 (.079) | |
|
| ||||||
| G4 | Intercept | 6.0 | 5.979 (.290) | 5.979 (.290) | 5.989 (.308) | 5.963 (.319) |
| Linear lope | −0.6 | −0.609 (.104) | −0.609 (.104) | −0.620 (.141) | −0.595 (.077) | |
|
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| Condition 4: Decreased sample size (N = 300)
| ||||||
| G1 | Intercept | 5.0 | 4.991 (.098) | 4.991 (.098) | 4.991 (.098) | 4.991 (.098) |
| Linear lope | 0.1 | 0.095 (.032) | 0.095 (.032) | 0.095 (.032) | 0.095 (.032) | |
|
| ||||||
| G2 | Intercept | 3.0 | 3.010 (.167) | 3.010 (.167) | 3.010 (.169) | 3.010 (.169) |
| Linear lope | 0.5 | 0.503 (.055) | 0.503 (.055) | 0.503 (.055) | 0.503 (.055) | |
|
| ||||||
| G3 | Intercept | 7.0 | 6.980 (.196) | 6.980 (.196) | 6.980 (.197) | 6.980 (.157) |
| Linear lope | −0.1 | −0.095 (.063) | −0.095 (.063) | −0.095 (.063) | −0.095 (.018) | |
|
| ||||||
| G4 | Intercept | 6.0 | 5.959 (.331) | 5.959 (.331) | 5.947 (.341) | 5.940 (.372) |
| Linear lope | −0.6 | −0.607 (.105) | −0.607 (.105) | −0.595 (.137) | −0.588 (.085) | |
Note. The multi-group latent growth model was based on five indicator variables. Under the ‘Generated’ columns, estimates were from the data sets generated at the normative values. Under the ‘Missing’ and ‘Same’ columns, all the responses on the 5th time point in Group 4 were completely missing and had the same responses, respectively.