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st: Ordinal to interval assuming normality


From   Michael Ingre <[email protected]>
To   <[email protected]>
Subject   st: Ordinal to interval assuming normality
Date   Thu, 16 Oct 2003 10:09:31 +0200

Dear Statalist

1) Is there any way to recode an ordinal variable to an interval scale if
you can assume that the latent variable that you are measuring are normally
distributed?

My problem is that I have variables (for example the occurrence of sleep
problems in five categories 1-5) that are skewed or have less than perfect
kurtosis. However, because I can assume that the latent variable is normally
distributed in the measured population the violations against normality in
my data should be due to errors in my instrument. More specifically, the
categories are not equally spaced. It should be possible to recode the value
of my categories so that my data would fit the normal distribution and as a
consequence the categories should be equally spaced on an interval scale.

2) If this is possible, would you consider this approach to be statistically
valid when interpreting for example Pearson correlation coefficients between
two recoded variables?

Thank You

Michael Ingre

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