I am running a generalised linear model in R. I have a single response variable and a maximum of 4 possible explanatory variables. I am adding each explanatory variable to the model sequentially, based on whether the coefficient is statistically significant.
If the coefficient for an explanatory variable is statistically significant at 0.05, the explanatory variable remains in the model. If the coefficient for an explanatory variable is NOT statistically significant at 0.05, the explanatory variable is removed from the model.
I am wondering if instead of using 0.05, I should be using a Bonferroni corrected P value? Should I use a threshold of 0.05/4 = 0.0125?