Standardized odds ratios

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Standardized odds ratios

Greg
Is there a way to standardize odds ratios in spss? If so, any suggestions?

Thanks
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Re: Standardized odds ratios

PRogman
Did you try Google?
See Karl L. Wuensch page
Standardizing Continuous Predictors In Binary Logistic Regression at
http://core.ecu.edu/psyc/wuenschk/MV/multReg/Logistic-Standardize.doc
The odds ratio tells one by what multiplicative factor the odds of the predicted event ...
Standardizing the continuous predictor variables puts them on the same ...

or
How to Get Standardized Regression Coefficients When Your Software Doesn’t Want To Give Them To You
http://www.theanalysisfactor.com/how-to-get-standardized-regression-coefficients/
Standardized regression coefficients remove the unit of measurement of predictor ...
You can then interpret your odds ratios in terms of one standard deviation ...


HTH
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Re: Standardized odds ratios

Bruce Weaver
Administrator
Karen Grace-Martin's note (second link given by PRogman) lists some of the advantages of standardized coefficients.  But they are not a cure-all.  The following is a note I wrote while reading John Fox's comments on standardized coefficients.  

HTH.

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In his book "Applied Regression Analysis and Generalized Linear Models" (2008, Sage), John Fox is very cautious about the use of standardized regression coefficients. He gives this interesting example. When two variables are measured on the same scale (e.g.,years of education, and years of employment), then relative impact of the two can be compared directly. But suppose those two variables differ substantially in the amount of spread. In that case, comparison of the standardized regression coefficients would likely yield a very different story than comparison of the raw regression coefficients. Fox then says:

"If expressing coefficients relative to a measure of spread potentially distorts their comparison when two explanatory variables are commensurable [i.e., measured on the same scale], then why should the procedure magically allow us to compare coefficients [for variables] that are measured in different units?" (p. 95)

Good question!

A page later, Fox adds the following:

"A common misuse of standardized coefficients is to employ them to make comparisons of the effects of the same explanatory variable in two or more samples drawn from different populations. If the explanatory variable in question has different spreads in these samples, then spurious differences between coefficients may result, even when _unstandardized_ coefficients are similar; on the other hand, differences in unstandardized coefficients can be masked by compensating differences in dispersion." (p. 96)

And finally, this comment on whether or not Y has to be standardized:

"The usual practice standardizes the response variable as well, but this is an inessential element of the computation of standardized coefficients, because the _relative_ size of the slope coefficients does not change when Y is rescaled." (p. 95)

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PRogman wrote
Did you try Google?
See Karl L. Wuensch page
Standardizing Continuous Predictors In Binary Logistic Regression at
http://core.ecu.edu/psyc/wuenschk/MV/multReg/Logistic-Standardize.doc
The odds ratio tells one by what multiplicative factor the odds of the predicted event ...
Standardizing the continuous predictor variables puts them on the same ...

or
How to Get Standardized Regression Coefficients When Your Software Doesn’t Want To Give Them To You
http://www.theanalysisfactor.com/how-to-get-standardized-regression-coefficients/
Standardized regression coefficients remove the unit of measurement of predictor ...
You can then interpret your odds ratios in terms of one standard deviation ...


HTH
--
Bruce Weaver
bweaver@lakeheadu.ca
http://sites.google.com/a/lakeheadu.ca/bweaver/

"When all else fails, RTFM."

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