The last step table is indeed the end result of the "stepwise regression". The caveat here is that usually you don't want to use this approach when there is a principled way to approach your model …

In R stepwise forward regression, I specify a minimal model and a set of variables to add (or not to add):

6 How does the stepwise regression method work for both direction in R with the step() function. I would think that one variable will be placed into the model and then another that will improve the measuring …

May 11, 2014 · What is the critical p-value used by the step() function in R for stepwise regression? I assume it is 0.15, but is my assumption correct? How can I change the critical p-value?

May 17, 2016 · Why is R adding the +disp in the 2nd step whereas the results are the same (AIC values and model selection values) as the backward selection. How is R exactly working in the stepwise …

Aug 17, 2016 · I am trying to use the step function in R. I want to use it with a binary variable as dependent variable. I use the following code: library (leaps) null=lm (SocEenz~1, data=dataScaled) …

May 18, 2021 · For this, I intend to use the step -function. However, I am unsure how exactly step deals with interactions. I want the selction procedure to be hierarchical in the following sense: If the …

I want to perform a stepwise linear Regression using p-values as a selection criterion, e.g.: at each step dropping variables that have the highest i.e. the most insignificant p-values, stopping wh...

Nov 16, 2018 · How to fit a robust step function to a time series? Ask Question Asked 7 years, 1 month ago Modified 7 years, 1 month ago

Oct 16, 2013 · Add the argument k=log(n) to the step function (n number of samples in the model matrix) From ?step: Arguments: ... k the multiple of the number of degrees of freedom used for the penalty. …