Role of Categorical Variables in Multicollinearity in the Linear Regression Model
نویسندگان
چکیده
The present article discusses the role of categorical variable in the problem of multicollinearity in linear regression model. It exposes the diagnostic tool condition number to linear regression models with categorical explanatory variables and analyzes how the dummy variables and choice of reference category can affect the degree of multicollinearity. Such an effect is analyzed analytically as well as numerically through simulation and real data application.
منابع مشابه
به‌کارگیری متغیرهای پنهان در مدل رگرسیون لجستیک برای حذف اثر هم‌خطی چندگانه در تحلیل برخی عوامل مرتبط با سرطان پستان
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