Thanks Cox and Heather. Regarding Cox's comment, this is a EQ5D(European
Quality of life) measurement. The result is in a continumm, but it is
possible to have a maximum of 243 values in the range of -0.6 to 1.0 (it
was mistake writing -1.6 earlier). We are using this EQ5D score as a
measure of health effect of two kinds of treatment, we are using markov
models to capture the movements between different health states (based on
EQ5D scores) in a life time perspective using multi-state life tables.
Regarding Heathers suggestion, Minimal important Difference (MID) or the
clinically meaningful threshold, I have been thinking about it, It would
be about .1, which will create too many states out of it. But this idea is
under consideration, and I am working on it.
The question still is: Is there any statistical methods? what I am
thinking is to start with 3 states arbitrarily defining cut points with at
least .10 difference between two cutoffs and then lookin at some outcome
(?? variance..standard error..)... then continuing to 4..5..6..7. .. I am
looking for some outcome which will be used in decision of number of
states and cutoffs...
Thank you and hope to get some response
SAMIR
Heather Gold wrote:
If you have some knowledge or information about what increment poses a
clinically meaningful threshold, that could be used as a cutpoint (e.g.,
every half point has an impact on a person's health somehow, and so you
create categories such as -1.5-(-1), -1-(-.5), -.5-0, 0-.5, .5-1).
Another option is to create "automatically determined" categories such as
tertiles but that is arbitrary, so you might want to create, say,
tertiles and quartiles and test if creating the categories in that manner
makes a difference.
At 10:42 AM 6/16/2004, you wrote:
I have a discrete variable (health status) which takes value from -1.6
to 1. The data consists of pre and post values of the variable. I want
to categorize the variable in 3-7 categories in order to study the
movement between categories . How can I do this? What Criteria should I
use to determine the best categorization, in terms of 1. number of
categories and, 2. cutoffs. Please respond.
Samir
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