Contents
Is the intercept important?
The Importance of Intercept The intercept (often labeled as constant) is the point where the function crosses the y-axis. In some analysis, the regression model only becomes significant when we remove the intercept, and the regression line reduces to Y = bX + error.
Is the intercept meaningful?
In this model, the intercept is not always meaningful. Since the intercept is the mean of Y when all predictors equals zero, the mean is only useful if every X in the model actually has some values of zero. So while the intercept will be necessary for calculating predicted values, it has to no real meaning.
What happens when you remove the intercept of a variable?
As you can see, by removing the intercept almost all the variables become significant with p-values less than 0.05, and most importantly the R2 value increases considerably. An R2 of 0.81 means that 81 percent of the variance in Y is predictable from the independent variables; and an R2 of 0.98 means that 98 percent is predictable; and so on.
When do I need to remove the intercept?
If the nature of what you are modeling is such that you want to assume this, then you might want to remove the intercept. This can usually be done by adding a NOINT option. * For software releases that are not yet generally available, the Fixed Release is the software release in which the problem is planned to be fixed.
Can a highly significant intercept be removed from a model?
So, a highly significant intercept in your model is generally not a problem. By the same token, if the intercept is not significant you usually would not want to remove it from the model because by doing this you are creating a model that says that the response function must be zero when the predictors are all zero.
When is it OK to remove the intercept in a linear regression?
If not the other regression parameters will be biased even if intercept is statistically insignificant (strange but it is so, consult Brooks Introductory Econometrics for instance). Finally, as I do often explain to my students, by leaving the intercept term you insure that the residual term is zero-mean.