RE: LNT models -Radon/smoking

["Bradshaw, Keith" <Keith.Bradshaw@nnc.co.uk>]

	<SNIP>
> > Following this thread I see discussions of confounding factors that are
> > difficult to control for because they are non-linear.
	<SNIP>

> 	--My study avoids the problem of non-linearity by using
> "Stratification". For example, if one worries about population density as
> a confounding factor, I do a complete analysis utilizing only data from
> counties that have nearly the same population density. I do this for many
> different population densities, and I always get the same result, without
> assuming that anything is linear with population density.
> 	The reason I am able to do this is because I have 1600 counties in
> my data files, whereas 160 counties is enough for doing a complete
> analysis with little statistical uncertainty. 
> 	I also have a treatment of multiple confounding factors, but that
> is too complex to summarize here. 
> 
	<SNIP


	I've not been able to keep up with all the correspondence on this
thread, and I have not seen the studies it relates to, so apologies if I'm
going over old ground.  But this point reminds me I was going to say a  week
ago.

	If the major cause of lung cancer is smoking, it's inevitable that
the uncertainty in lung cancer yield from this causes a great deal of
statistical noise in the smaller effect that you are trying to measure, i.e.
lung cancer yield from radon in homes.  So why not discount all households
that have one or more resident smokers (including people who have given up
in the last 20 or 30 years).  I realise  this will wipe out the majority of
the data set but it might be better to do this than attempt to correct for
it, especially since you appear to have a large study.

	Regards

	keith.bradshaw@nnc.co.uk












	END




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