Re: [R] Factorial regression with multiple features: how to remove non-significant features?

Hi Parthiban, I urge you to rethink your approach, or at least proceed with extreme caution. Lower-order terms involved in higher-order interactions may not be what you think they are. And there are serious problems with stepwise model selection. I encourage you to read a good regression modeling

[R] Factorial regression with multiple features: how to remove non-significant features?

Hello all, I am trying to do factorial regression using lm() like this (example): model<-lm(y ~ x1 + x2 + x3 + x4 + x1*x2*x3*x4) The final term 'x1*x2*x3*x4' adds all possible interactions between explanatory variables to the model. i.e. x1:x2, x1:x2:x3, etc, etc. Now, the issue is that some of