On 21 Jan 2002 16:53:31 -0800, [EMAIL PROTECTED] (Wuzzy) wrote: > Pretend you want to see how fat relates to cancer risk > > fat Kcal cancer > 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 for KCal, but how is this done, is the following > the BEST way?
The problem is *nonsense* as it is stated, since fat= KCal except for the measurement units. Adjusting A for A', where A' is approximately A except for irrelevant measurement error, you have essentially nothing left. Ever. You always have to be careful when you adjust for something that has much correlation, to be sure that the direction of the logic thoroughly makes sense. (If there is not much correlation, then there is not much change possible in the estimator -- though a *test* could become more significant if a bunch of error variance is accounted for.) A simple way to "adjust for sex" (for instance), is to compute a statistic for each sex separately, and then average. "Within group" is the basic idea of adjusting. [ ... ] > 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." > above? Studies often cite how they have "adjusted" for KCal, is this > the way they do it, they usually do not specify the method. The method is there, ordinarily, in the articles I read. It is a poor journal (I think..., I estimate blindly ...) that does not require a statement of that method, but if you know nothing of regression, etc., you won't recognize the statement when it appears. -- Rich Ulrich, [EMAIL PROTECTED] http://www.pitt.edu/~wpilib/index.html ================================================================= Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at http://jse.stat.ncsu.edu/ =================================================================
