The process of backward elimination can be broken down into the following steps:
Start with All Variables: Begin with a model that includes all potential independent variables. Identify the Least Significant Variable: Perform a statistical test (e.g., t-test, F-test) to identify the variable with the highest p-value. Remove the Least Significant Variable: Remove the variable with the highest p-value from the model. Re-fit the Model: Re-fit the model without the removed variable and repeat the process. Stop When All Remaining Variables are Significant: Continue the process until all remaining variables have p-values below a pre-defined significance level (e.g., 0.05).
