Abstract

Abstract: The presence of high correlation among predictors in regression mode has undesirable effects on the regression estimating. In the literature, there are several available biased methods to overcome this issue. The Poisson regression model (PRM) is a special model from the generalized linear models. The PRM is a well-known model in research application when the response variable under the study is count data. Numerous biased estimators for overcoming the multicollinearity in Poisson regression model have been proposed in the literature using different theories. An overview of recent biased methods for PRM is provided. A comparison among these biased estimatorsallows us to gain an insight into their performance. Simulation and real data application results show that the Liutype estimator is comparable to other estimators.

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The article was added to IASJ on 2022-05-15

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