Table 1.
SEs and CIs for GMA ds from Linear Models as a Function of Estimation Methods
| Covariates in Example 6.10 Dataset Included in the Linear GMA |
||||||||
|---|---|---|---|---|---|---|---|---|
|
x1 Only |
All 3 Covariates |
|||||||
| SE | 95% CI | SE | 95% CI | SE | 95% CI | SE | 95% CI | |
| Mplus Outputted CI | ||||||||
| delta method | .134 | .767, 1.294 | .136 | .746, 1.279 | .133 | .734, 1.255 | .105 | .666, 1.078 |
| pbootstrap | .132 | .756, 1.291 | .134 | .741, 1,278 | .131 | .724, 1.252 | .104 | .679, 1.074 |
| rbootstrap | .131 | .764, 1.270 | .133 | .762, 1.273 | .129 | .748, 1,255 | .096 | .676, 1.070 |
| Transformation of CI of b to CI of d | ||||||||
| delta method | NA | .767, 1.293 | NA | NA, NA | NA | NA, NA | NA | .666, 1.078 |
| pbootstrap | NA | .755, 1.291 | NA | NA, NA | NA | NA, NA | NA | .680, 1.074 |
| rbootstrap | NA | .763, 1.271 | NA | NA, NA | NA | NA, NA | NA | .676, 1.070 |
Note. GMA = growth modeling analysis, N =500. SE = standard error; CI = 95% confidence interval, pbootstrap = percentile (standard) bootstrap, rbootstrap = residual bootstrap, SD1 = 1.748, SD2 = SD estimated with y 11 residual variance, SD3 = SD estimated with mean of all y (y11-y14) residual variances, NA = not applicable. CIs for time-varying GMA ds from the single covariate model (x1 only) cannot be compared with respective CIs from the multiple covariates model (using 3 covariates) because point estimates differ between the two types of models.