Wuzzy wrote:
>
> > Walter Willett has a whole chapter on this subject in his book Nutritional
> > Epidemiology. It should be considered required reading before attempting to
> > model anything that has to do with diet.
>
> Thanks this is a really good book, not just for ppl wanting to study
> n
Hi
On 30 Jan 2002, Wuzzy wrote:
> Anyway I'm currently going on the definition of "adjusted" for 1 2 and
> 3 as the following equation:
>
> adjusted variable=variable^-variable
>
> (where variable-hat represents the variable predicted by 1 2 and 3 in
> a multivariate equation and "variable" is
> Walter Willett has a whole chapter on this subject in his book Nutritional
> Epidemiology. It should be considered required reading before attempting to
> model anything that has to do with diet.
Thanks this is a really good book, not just for ppl wanting to study
nutrition but surveys in gen
David Heiser wrote:
> I find it extremely difficult to interpret multivariate equations.
> Are there any good books on conceptualizing the equation?
Modelling the effects of macronutrients on risk of disease is complicated
because the sum of the macronutrients in the diet equal the total energ
-Original Message-
From: [EMAIL PROTECTED]
[mailto:[EMAIL PROTECTED]]On Behalf Of Wuzzy
Sent: Thursday, January 24, 2002 3:30 PM
To: [EMAIL PROTECTED]
Subject: Re: how to adjust for variables
I find it extremely difficult to interpret multivariate equations.
Are there any good books
> [ ... ]
> > Is doing a univariate regression between the variable you want to
> > adjust for and your predictor the only way to adjust for values as
>
> Univariate? Absolutely not. *Multiple* regression gives
> "partial regression coefficients." Those "adjust."
>
I find it extreme
On 21 Jan 2002 16:53:31 -0800, [EMAIL PROTECTED] (Wuzzy) wrote:
> Pretend you want to see how fat relates to cancer risk
>
> fat Kcalcancer
> 1 2 100
> 2 4 120
> 3 6 130
> 4 8 140
> 5 10 150
> 6 12 160
> 7 14 170
> 8 16
Pretend you want to see how fat relates to cancer risk
fat Kcalcancer
1 2 100
2 4 120
3 6 130
4 8 140
5 10 150
6 12 160
7 14 170
8 16 180
9 18 190
10 20 200
You have to adjust
also if you ajdust by using residuals, do you still have to factor in
KCal in your final regression equation?
it would seem to me that you should if you have other variables that
might be confounded by KCal, but otherwise you wouldn't.
===