Applications of OPLS Statistical Method in Medicine

Studies related to prognosis in medicine result in a large volume of variables if clinical and laboratory variables are simultaneously accompanied with new imaging techniques; this issue causes problems for classical statistical methods such as logistic and linear regression. Among these cases, emergence of multicollinearity or close linear correlation between regression variables when the number of regression variables is high can be pointed out. Emergence of multicollinearity is inappropriate for ordinary least squares of regression model. PLS is a well-known method for connecting two X and Y data matrices using a multicollinearity model. OPLS is the product of a change which has occurred on PLS method in recent years. Considering application problems of linear regression method, applying an alternative method is a requirement. Using OPLS method can reduce model complexity and develop its power.