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Biased Estimators in Zero-Inflated Poisson Regression Model in the Presence of Multicollinearity: Subject Review | ||
| College Of Basic Education Research Journal | ||
| Volume 20, Issue 1, March 2024, Pages 819-842 PDF (728.53 K) | ||
| Document Type: Research Paper | ||
| DOI: 10.33899/berj.2024.182779 | ||
| Authors | ||
| Nadwa Khazal Rashad* 1; Nawal Mahmoud Hammoud* 2 | ||
| 1Department of Management Information Systems/ College of Administration and Economics/ University of Mosu | ||
| 2Department of Management Information Systems/ College of Administration and Economics/ University of Mosul | ||
| Abstract | ||
| The problem of multicollinearity, which occurs as a result of high correlation and linear dependence between two or more explanatory variables in a model, is one of the most important issues in model building, negatively affecting the parameter estimation process of the regression model. This study aims to review the shrinkage estimators used to address the problem of multicollinearity that appears in the zero-inflated Poisson regression model. This model is one of the most commonly used models when the response variable data have countable values and are not normally distributed. Through Monte Carlo simulation experiments, it was found that the shrinkage estimator with two parameters is the best proposed estimator due to its reduction of the model's mean square error. | ||
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