st: Re: Nonparametric two way ANOVA

[Roger Newson <roger.newson@kcl.ac.uk>]

At 11:28 05/02/04 -0500, Joseph Wagner wrote:

> I want to do what I know is a pretty simple calculation but I am constrained
> by my dependent variable which is non-normal.
>
> I wish to see if there are differences in viral load stratified by age
> category and by race.  Viral load is not normal and in my case, I cannot
> transform this variable to approximate normal.
>
> I know I could do kruskal wallis or trend tests by race and by age category
> individually but I need to do both.
>
> If viral load were normal, I could do:
>
> anova vload agecat race
>
> The Friedman test is the only thing that comes to mind but I don't think
> this is what I want.
In my experience, viral loads are lognormally distributed. I would 
therefore log-transform the viral loads and use linear regression methods 
on the logs to estimate geometric means and their ratios, using the 
-eform()- option of -regress-. For instance:

gene logvload=log(vload)
gene byte baseline=1
xi:regress vload i.agecat i.race baseline, noconst robust eform(GM/Ratio)

The parameter -baseline- will then be a baseline geometric mean viral load, 
representing geometric mean viral load for individuals with the reference 
age category and race category. The other parameters will be ratios of 
geometric mean viral load in other race and age categories, compared to the 
baseline category. The effect of race and age are assumed to be multiplicative.

We need to generate the variable -baseline- and use the -noconst- option of 
-regress-, because, if we use the -sform- option without the -noconst- 
option, then Stata does not print the intercept, which in this case is the 
baseline geometric mean. Using the variable -baseline- with the -noconst- 
option, we can fool Stata into thinking there is no intercept for it to hide.

I hope this helps.

Roger


--
Roger Newson
Lecturer in Medical Statistics
Department of Public Health Sciences
King's College London
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Tel: 020 7848 6648 International +44 20 7848 6648
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Email: roger.newson@kcl.ac.uk
Website: http://www.kcl-phs.org.uk/rogernewson

Opinions expressed are those of the author, not the institution.

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