Re: Inter-instrument agreement
- From: mcap <mcam54@xxxxxxxxx>
- Date: Thu, 27 Dec 2007 18:40:50 -0800 (PST)
On Dec 21, 9:19 am, AMY <andrea.me...@xxxxxxxxx> wrote:
Inter-instrument agreement is often measured using the intra class
correlation coefficient (ICC). Here, I want to know whether the
agreement between two instruments (or methods), let's call them y1 and
y2, varies with a third variable (=x) that is continuously
distributed. As an example one might be interested in knowing whether
the agreement between the self-reported number of binges in a given
time interval and the corresponding number using ecological momentary
assessment (EMA) is negatively related to the subject's BMI. If the
covariate was categorical, I could simply compute the ICC for each
category separately. In the case of a continuous covariate this is
obviously not possible unless I categorize the covariate beforehand
(at the cost of reduced power). My idea is now to compute a kind of
index, such as the difference between y2 and y1 and regress it against
x using the formula y2-y1=a+b*x. This is the same as using a multiple
regression model in which the coefficient of y1 is forced to be one:
y2=a+b*x+1*y1. Another, and maybe more useful model because it more
directly addresses the question at hand, would be: y2=a+b*x
+c*y1+d*x*y1. In this model one would primarily be interested in the
interaction coefficient d which tests whether the relationship between
y2 and y1 is moderated by x.
As I am unsure about how to proceed in this matter I would be grateful
to any comments regarding these thoughts, including references that
help me getting on.
Many thanks in advance
AMY
Not my area...but....Since the ICC is based on the repeated measures
anova, could you use a repeated measures ANCOVA??
.
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