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Ok, it is known that stepwise LR isn't validstepwise LR isn't valid, and forward LR fails to capture the combination of the variables (sometimes a independent variable will become significant only in the presence of the other variables), when backward elimination resolves very well this kind of problem.

So is it true when we say backward is the best strategy between the three methods?

Ok, it is known that stepwise LR isn't valid, and forward LR fails to capture the combination of the variables (sometimes a independent variable will become significant only in the presence of the other variables), when backward elimination resolves very well this kind of problem.

So is it true when we say backward is the best strategy between the three methods?

Ok, it is known that stepwise LR isn't valid, and forward LR fails to capture the combination of the variables (sometimes a independent variable will become significant only in the presence of the other variables), when backward elimination resolves very well this kind of problem.

So is it true when we say backward is the best strategy between the three methods?

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Is it true when we say that Backward is better than Forward and Stepwise Logistic Regression?

Ok, it is known that stepwise LR isn't valid, and forward LR fails to capture the combination of the variables (sometimes a independent variable will become significant only in the presence of the other variables), when backward elimination resolves very well this kind of problem.

So is it true when we say backward is the best strategy between the three methods?