-----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 on conceptualizing the equation?
For instance:
If you are assessing whether protein, fat, or carbohydrate is
important in obesity independant of calories, do you do the following
model:
Disease=carb+proten+fat+calories
and if so, isn't the word "calories" meaningless as it is equal to the
sum of the other three.
Perhaps it should not be included in the model.
I have read of studies were they will use everything except "carb" as
follows:
disease=protein+fat+calories
and from here you can determine what substituting carb with protein or
fat will have on the disease.
It is very difficult to conceptualize and very difficult to understand
what the word "calories" means anymore in a multivariate model..
It seems if you use univariate adjusted values it is easier to model,
I have very little experience in statistics as everyone can tell..
Just commenting, no real question here.. I will probably understand
it with time..
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The points that Wuzzy makes here illustrate one of the difficulties of model
building.
There are two ways to adjust. I will illustrate below using totally
artificial numbers, because I don't have my handbooks in front of me that
has realistic values.
Assume we have a subject:
Assume subject consumed 120 grams of fat (with a calorie content of 20
cals/gram), 211 grams of protein (with a calorie content of 15 cals/gram)
and 350 grams of starch (with a calorie content of 33 cals/gram):
I. Adjust for a total calorie level of 10,000 calories per day: Multiply
each by 10000/16715 gives an adjusted fat consumption of 71.8 grams, protein
of 126.2 grams and starch of 209.4 grams. The three X values then would be
71.8, 126.2 and 209.4 rather then the actual values of 120, 211 and 350
grams
II. Adjust for individual calorie levels (15,10,20): Multiply 120 times
20/15 to give a standard fat intake of 133.3 grams. Do the same for the
others to get (211*15/10=316.5) and (350*33/20=412.5). The three X values
would then be 133.3, 316.5 and 412.5 rather than the actual values of 120,
211 and 350 grams.
This of course ignors the really important attributes that may correlate to
the disease, such as this:
Fat
Saturated
Unsaturated
Animal
Vegtable
Calories (heat of combustion, higher or lower)
Thermal processed
Chemical and physical modifications (i,e, hydogenation, extraction, low
temperature filtering, etc.)
Protein
Animal
Vegtable
Fraction of added chemicals (i.e. Lysine)
Thermal processed
Calories
Carbohydrates
Starch from cereals
Cellulose
Hydolyzed cellulose
Starches from animal sources
Water soluble sugars (Sucrose)
Polysacharides
Chemically generated sugars (i.e. corn starch derived sweeteners)
Thermally processed starches
Calories (heat of combustion)
Chemically esterified starches
If you are going to measure the amount of fat by a calorie measure, this
excludes all the other attributes.
DAHeiser
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