TABLE 8.
Simulation study 2: bias and RMSE for the latent correlation as a function of the distribution of the observed variables (skewness and kurtosis) and the sample size.
| Bias |
RMSE Gain |
||||||||||||||
| skew/kurt | N | PML | PMLR | ULS | ULSR | MAP | Med | EAP | PML | PMLR | ULS | ULSR | MAP | Med | EAP |
| 0/0 | 30 | −0.065 | −0.067 | −0.010 | −0.011 | −0.003 | −0.131 | −0.154 | 100 | 101 | 99 | 101 | 116 | 80 | 77 |
| 50 | –0.019 | –0.020 | 0.016 | 0.017 | –0.018 | −0.085 | −0.092 | 100 | 101 | 96 | 98 | 114 | 85 | 82 | |
| 100 | –0.014 | –0.016 | 0.008 | 0.008 | −0.051 | −0.063 | −0.061 | 100 | 101 | 94 | 95 | 116 | 95 | 92 | |
| 500 | –0.002 | –0.002 | 0.002 | 0.001 | –0.011 | –0.012 | –0.013 | 100 | 101 | 99 | 100 | 102 | 101 | 101 | |
| 0/3 | 30 | –0.038 | –0.033 | 0.000 | 0.007 | 0.027 | −0.106 | −0.130 | 100 | 100 | 101 | 98 | 119 | 80 | 77 |
| 50 | –0.042 | –0.036 | 0.002 | 0.001 | –0.037 | −0.102 | −0.109 | 100 | 98 | 97 | 94 | 108 | 84 | 81 | |
| 100 | –0.007 | –0.004 | 0.015 | 0.016 | –0.041 | −0.058 | −0.056 | 100 | 94 | 96 | 91 | 117 | 95 | 92 | |
| 500 | –0.003 | –0.005 | 0.001 | –0.002 | –0.011 | –0.013 | –0.014 | 100 | 97 | 99 | 95 | 104 | 101 | 101 | |
| 0/7 | 30 | –0.043 | –0.024 | 0.007 | 0.016 | 0.024 | −0.108 | −0.133 | 100 | 95 | 101 | 98 | 116 | 82 | 79 |
| 50 | –0.021 | –0.011 | 0.019 | 0.021 | –0.021 | −0.085 | −0.092 | 100 | 96 | 97 | 93 | 115 | 87 | 84 | |
| 100 | –0.004 | –0.004 | 0.018 | 0.013 | –0.037 | −0.054 | −0.052 | 100 | 92 | 98 | 89 | 117 | 94 | 91 | |
| 500 | –0.003 | –0.002 | 0.001 | 0.002 | –0.012 | –0.013 | –0.014 | 100 | 92 | 99 | 91 | 101 | 100 | 101 | |
| 1/3 | 30 | –0.048 | –0.046 | 0.003 | 0.004 | 0.026 | −0.110 | −0.136 | 100 | 99 | 103 | 99 | 119 | 81 | 79 |
| 50 | –0.023 | –0.018 | 0.016 | 0.019 | –0.019 | −0.086 | −0.093 | 100 | 98 | 95 | 94 | 111 | 82 | 79 | |
| 100 | –0.006 | –0.012 | 0.013 | 0.008 | –0.042 | −0.055 | −0.054 | 100 | 99 | 94 | 93 | 116 | 96 | 92 | |
| 500 | 0.002 | –0.002 | 0.005 | 0.001 | –0.006 | –0.008 | –0.009 | 100 | 97 | 99 | 96 | 103 | 101 | 101 | |
| 2/7 | 30 | –0.015 | –0.009 | 0.033 | 0.029 | 0.064 | −0.078 | −0.105 | 100 | 95 | 99 | 93 | 114 | 77 | 74 |
| 50 | –0.017 | –0.017 | 0.017 | 0.001 | –0.014 | −0.079 | −0.086 | 100 | 94 | 97 | 94 | 113 | 87 | 84 | |
| 100 | –0.003 | –0.015 | 0.015 | 0.001 | –0.035 | −0.051 | –0.049 | 100 | 93 | 98 | 89 | 117 | 96 | 93 | |
| 500 | 0.003 | –0.014 | 0.007 | –0.011 | –0.006 | –0.007 | –0.008 | 100 | 95 | 99 | 94 | 103 | 100 | 100 | |
RMSE = root mean square error. PML = penalized maximum likelihood; PMLR = penalized maximum likelihood with robustly estimated covariance matrix; ULS = unweighted least squares; ULSR = unweighted least squares with robustly estimated covariance; MAP = mode of marginal posterior; Med = median of marginal posterior; EAP = mean of marginal posterior; μρ = prior guess for latent correlation; νρ = prior sample size for latent correlation; skew = skewness; kurt = kurtosis; Biases smaller than –0.05 or larger than 0.05 are printed in bold. For the RMSE gain, the RMSE of PML estimation is used as a reference method; values smaller than 100 indicate that the RMSE of the respective method is lower than the RMSE of the reference method. The true correlation and loadings were set to ρ = 0.50 and λ = 0.50, respectively.