The Use of Robust Criteria in Selecting Effective Variables in Linear Regression Model for Blood Sugar Analogy

The research deals with the topic of variable selection in linear regression using robust procedures as resistant to outliers and other failures of assumptions . The objective of the research is using robust criteria (RAIC , RSIC, RCp, RVC, RSC, RF, RAPE) in selection of most adequate independent variables in the regression model used to estimate blood sugar as dependent variable and other independent variables and comparing the performance of these criteria. The results shows that the RAPE criterion was the best in selecting the most important variable compared with the other criteria.