wuzzy <[EMAIL PROTECTED]> wrote: > It is clear that sampling a person for a serum value in one shot will > not give you a correct account of the population's serum distribution > My own belief is that you *can* use single-shot serum values to > predict disease risk: but you have to use group these with a value > that has areliable distribution: ex. group serum cholesterol by > subject's bodyweight, which does not vary appreciably among > individuals.
> For instance divide your subjects into those with high bodyweight and > low bodyweight and use t-test to compare means of cholesterol levels. > Is there any criticisms to the above: the t-test should be sufficient > Any info, references (journals or books) appreciated. You will still have dilution of the true strength of the association. See Qizilbash et al AJE 1991 133:832-8 for one example of a case-control study with modelling of measurement error. Bollen _Structural equations with latent variables_ is a nice intro to measurement models. There are a lot of Bayesian approaches to the problem. A Medline search for "measurement error relative risk" will give some recent examples eg Rosner & Gore Am J Epidemiol 2001 154:827-35 (Rosner has written much on the topic). You can use a single measurement to make disease risk assessment, -- there are lots of papers on this eg single random blood glucose criteria for diabetes, single blood pressure reading for hypertension, single cholesterol measurement for CHD risk. -- | David Duffy. ,-_|\ | email: [EMAIL PROTECTED] ph: INT+61+7+3362-0217 fax: -0101 / * | Epidemiology Unit, The Queensland Institute of Medical Research \_,-._/ | 300 Herston Rd, Brisbane, Queensland 4029, Australia v . . ================================================================= Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at: . http://jse.stat.ncsu.edu/ . =================================================================
