Ali,
(1) You can use independent variables measured on different scales in a single multiple regression.
(2) The requirement for normality is a requirement for the distribution of residuals of the regression, not a requirement for the distribution of the independent variables. This being said, in general, if the independent variables are normally distributed it is more likely that the residuals will be normally distributed. After performing a regression it is always wise to look at the distribution of the residuals to make sure that they conform to the normality assumption.
John
John Sorkin M.D., Ph.D.
Chief, Biostatistics and Informatics
Baltimore VA Medical Center GRECC and
University of Maryland School of Medicine Claude Pepper OAIC
University of Maryland School of Medicine
Division of Gerontology
Baltimore VA Medical Center
10 North Greene Street
GRECC (BT/18/GR)
Baltimore, MD 21201-1524
410-605-7119
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>>> "Ali A. Bromideh" <[log in to unmask]> 01/09/06 4:33 AM >>>
A friend of mine has got two enquiries about regression, would you please
help him on these questions? You can simply reply to me, NOT to AllStat!
"...Some methodology books talk about using dummy variables (nominal or
ordinal scales) in regression, my question is that: can I use dummy
variables together with interval variables in the one multiple regression
test (e.g. see if sex (male/female), salary, and age affect level of
creativity in advertising). I personally don't feel that it is right to use
both types of scales in one multiple regression test, but I still didn't
find luck in finding a reference to support that ( I might be wrong). Any
help!
The other question is about the normality assumption in regression, some
scholars say that only the dependent needs to be normally distributed, and
that it is ok if the independent is not normal. Does any one have a strong
argument (reference) to support or reject this opinion? ..."
Regards,
ALI
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