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Standardized beta-coefficients in regression

2 messages · Jeroen Ooms, Frank E Harrell Jr

#
Unfortunately I found myself in the same position as outlined above, where I
was requested to reproduce 'standardized regression coefficients' as
reported by SPSS. Below an example that produces something very similar to
the results table from an SPSS "Linear Regression" procedure, including the
standardized regression coefficients:

mylm <- lm(Sepal.Width ~ ., data=iris, x=TRUE, y=TRUE)
sd.x <- sd(mylm$x);
sd.y <- sd(mylm$y);
std.coef <- coef(mylm) * (sd.x / sd.y);
coef.table <- as.data.frame(summary(mylm)$coefficients);
coef.table <- cbind(coef.table, std.coef);
print(coef.table);

I do agree with B.R. but unfortunately the life of an applied statistician
is complex sometimes :-)

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#
It is true that our lives are complex but we have to stick to principles. 
Plus, statisticians have the lowest unemployment rate in all of the sciences
(1% according to NSF from a poll taken 2 years ago) so we should be able to
capitalize on that by sticking to well-founded beliefs and facts and
choosing positions were respect for our expertise is a given.

Standardized coefficients cloud rather than clarify, and they only apply to
the trivial case where everything is linear. See
http://biostat.mc.vanderbilt.edu/ManuscriptChecklist for more information.
Frank
Jeroen Ooms wrote:
-----
Frank Harrell
Department of Biostatistics, Vanderbilt University
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