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Sensitivity Analysis of Diagnostic Measures to the Liu Biasing Parameter and Error Distribution in Linear Mixed Measurement Error Models | ||
| Journal of Advances in Statistical Learning and Data Analysis | ||
| مقالات آماده انتشار، پذیرفته شده، انتشار آنلاین از تاریخ 24 مهر 1405 اصل مقاله (6.33 M) | ||
| نوع مقاله: Original Article | ||
| شناسه دیجیتال (DOI): 10.30473/jaslda.2026.79273.1009 | ||
| نویسندگان | ||
| Fatemeh Ghapani؛ Razieh Jafaraghaie* | ||
| Department of Mathematics and Statistics, Sho.C., Islamic Azad University, Shoushtar, Iran | ||
| چکیده | ||
| In this paper, we investigate the sensitivity of diagnostic measures to the Liu biasing parameter and error distribution assumptions in linear mixed measurement error (LMME) models when multicollinearity is present. We evaluate the performance of Cook’s distance for fixed effects, random effects, and conditional responses under different error distributions (Normal, heavy-tailed, and skewed). A parametric bootstrap procedure is used to obtain empirical distribution of the test statistic and a simulation study has been given to show the performance diagnostic criteria. The simulation study shows that the proposed methods maintain the Type I error rate close to the nominal level and exhibit high power, even under non-normal error distributions. The real data analysis, utilizing the Boston Housing dataset, demonstrates that the identification of influential points depends heavily on the Liu biasing parameter, emphasizing the need for sensitivity analysis in practical applications. | ||
تازه های تحقیق | ||
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| کلیدواژه‌ها | ||
| Case deletion model؛ Cook’s distance؛ Liu estimator؛ Measurement error؛ Multicollinearity | ||
| مراجع | ||
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