Robust Estimation Methods in Random Intercept Model: A Comparative Study | ||||
| The Egyptian Statistical Journal | ||||
| Article 5, Volume 62, Issue 1, June 2018, Page 70-92 PDF (7.89 MB) | ||||
| Document Type: Original Article | ||||
| DOI: 10.21608/esju.2018.244264 | ||||
 View on SCiNiTO | ||||
| Authors | ||||
| Hend A. Auda; Yahia S. El-Horbaty; Eman M. Hanafy | ||||
| Department of Mathematics, Insurance and Applied Statistics, Helwan University, Egypt | ||||
| Abstract | ||||
| Random Intercept regression models are used in modeling grouped data where the observations are correlated in each group. This paper present a comperative sinulation study between parametric and two robust estimation methods to assess the influence of the violation of the normality of the error distribution on the efficiency of the model peremeter estimates. The asymptotic relative efficiency is used under various factors including the number of groups, the group size and the intercalss correlation coefficient. The methos under consideration are applied to data on the faculty of social work's math-achievement at helwan university. | ||||
| Keywords | ||||
| Random Intercept regression model , restriced maximum likelihood estimation methos; robust estimation methods | ||||
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