Research Article
Development of New Robust Optimal Score Function for the Weibull Distributed Error Term in Multilevel Models
Table 5
Bias and MSE of
using Weibull, Wilcoxon, and REML methods when
ā=ā3.
.
| | REML | Weibull | Wilcoxon | Precision | N2 | N1 | Bias | MSE | Bias | MSE | Bias | MSE | Weib/REML | Weib/Wil | Wil/REML |
| 5 | 5 | 2.079 | 2.457 | 0.225 | 0.527 | 2.083 | 2.717 | 1.072 | 0.97 | 1.106 | 10 | 2.09 | 3.537 | 0.224 | 0.683 | 2.107 | 3.691 | 0.994 | 0.953 | 1.044 | 20 | 2.098 | 5.796 | 0.24 | 1.153 | 2.096 | 6.005 | 0.981 | 0.947 | 1.036 | 40 | 2.096 | 10.296 | 0.237 | 1.951 | 2.104 | 10.53 | 0.964 | 0.943 | 1.023 |
| 10 | 5 | 2.199 | 1.908 | 0.078 | 0.284 | 2.205 | 1.967 | 1.02 | 0.989 | 1.031 | 10 | 2.193 | 2.551 | 0.094 | 0.369 | 2.185 | 2.6 | 1.001 | 0.982 | 1.019 | 20 | 2.213 | 3.824 | 0.068 | 0.512 | 2.211 | 3.839 | 0.985 | 0.981 | 1.004 | 40 | 2.214 | 6.349 | 0.112 | 0.857 | 2.208 | 6.376 | 0.984 | 0.98 | 1.004 |
| 20 | 5 | 2.276 | 1.674 | 0.033 | 0.231 | 2.263 | 1.676 | 0.997 | 0.996 | 1.001 | 10 | 2.286 | 2.015 | 0.048 | 0.26 | 2.274 | 2.013 | 0.992 | 0.993 | 0.999 | 20 | 2.256 | 2.628 | 0.052 | 0.344 | 2.245 | 2.605 | 0.987 | 0.995 | 0.991 | 40 | 2.265 | 3.964 | 0.046 | 0.463 | 2.252 | 3.934 | 0.984 | 0.992 | 0.992 |
| 40 | 5 | 2.288 | 1.511 | 0.034 | 0.203 | 2.274 | 1.497 | 0.987 | 0.996 | 0.991 | 10 | 2.281 | 1.685 | 0.038 | 0.193 | 2.268 | 1.658 | 0.98 | 0.996 | 0.984 | 20 | 2.294 | 2.028 | 0.018 | 0.212 | 2.274 | 2.001 | 0.982 | 0.995 | 0.987 | 40 | 2.302 | 2.737 | 0.011 | 0.305 | 2.284 | 2.703 | 0.984 | 0.996 | 0.988 |
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