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From | Richard Williams <richardwilliams.ndu@gmail.com> |
To | statalist@hsphsun2.harvard.edu, statalist@hsphsun2.harvard.edu |
Subject | Re: st: Including constant? |
Date | Wed, 01 Jun 2011 10:41:54 -0500 |
At 07:23 AM 6/1/2011, lreine ycenna wrote:
Do we typically not have to include constants in regression tables when presenting them?
You can probably say most or all of what you want to say without including the constant. After all, how many times do you see a paper discussing the values of the constants?
But, I personally always include them. It is particularly useful if somebody wants to calculate a yhat value for some combination of values for the Xs. How useful the constant is as a standalone value depends on the coding of the Xs. The constant is the value someone would have if they had a value of 0 for every X. Often such a person cannot exist because one or more variables cannot take on a value of 0, e.g. nobody has 0 height, and nobody gets a score of 0 on a test scaled to range between 400 and 1600. However, if you center the Xs (subtract the mean from each case for each X) then the constant becomes the predicted score for a person who has average values on every X. Such a person (or someone close to it) may actually exist, making the constant more interpretable as a stand-alone number, i.e. the constant is the score a totally average person would be expected to have. Or, if the model just has dummy variables (female, black) then the constant could be the average score for, say, a male white.
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