A Method to Detect Influential Observations in Multiple Linear Regression Analysis

It is so important to determine outlier, influence and leverage points in multiple linear regression analysis for the accuracy of statistical inferences. To detect the influence observations, Nurunnabi et al. (2016) proposed a robust influence distance (ID). However, the determination of observations that would not be used in the calculations of this distance are based on non-robust statistics. Thus, it is affected by outliers. In this paper, it is suggested that influence distance based on robust estimators (RID) could be used for detecting influence observations. Moreover ID and RID’s which were used to determine outliers, are applied to two known data sets and are compared based on simulation studies. The results show that RID based on RLS performs the bes