# Solved – Cubic and linear relationships in multiple regression model

What is the correct way to fit a multiple regression model where I have a combination of cubic and linearly related independent variables?

If I transform the variable showing cubic relationship, how do I transform back the forecasted variable, given that it's the result of both non-transformed and transformed data sets?

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#### Best Answer

One way to fit the model is, as you guess in the comment, to transform \$X_1\$ first, then run a multiple linear regression. However, you don't have to do any transformation back to the predicted \$Y\$ value, since the regression is still using the untransformed \$Y\$ variable as the dependent variable. Let's say you create \$Z = X_1^3\$, then the regression becomes \$Y = beta_0 + beta_1 Z + beta_2 X_2 + e\$. The estimates and/or predictions you get out of the model with the transformed \$X_1\$ are still for \$Y\$.

There are other ways to fit the model, but the choice between fitting methodologies is, in this case, independent of the transform of \$X_1\$.

Edit: It has occurred to me that you may have meant a cubic relationship where \$Y^3 propto X_1\$. This is equivalent to \$Y propto X_1^{1/3}\$, and you can still just transform \$X_1\$ without having to transform \$Y\$ at all.

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