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Re: st: Interpreting conditional logistic regression equations using 2 similar types of matching.
On 6 Feabh 2007, at 23:40, Donald Spady wrote:
This may be a second posting. The first one did not seem to go
I'm not sure I understand this design. Children can have more than
one seizure, so is your case variable whether the child ever had a
seizure or never had a seizure, or are you doing a nested case-
control and matching a child in whom a seizure occurred with a child
of the same age in whom one did not occur?
on reading the FAQ I realized that I might have sent non-plain
copied the output from Stata using the copy table command rather
copy text command. Hopefully this one will work.)
I am looking at the effect of iron-deficiency anemia on the
likelihood of a
child having a seizure.
Age is a measure of exposure to risk. This, and the fact that cases
are defined by the occurrence of an event, suggest survival models
here rather than conditional logistic regression.
I am using clogit but have a problem in that I have
matched my case/control "group" variable (age) as either very tightly
matched (same month: "tight") or more loosely matched (up to 3 months
The whole age range of difference is 30 months, so 3
You are losing cases (output omitted) with both of your current
designs, which is going to lower your power and, I'm guessing, bias
the estimates in ways you can't predict but have certainly demonstrated.
months is still fairly closely matched. When I do the 2 clogit
get different Odds ratios (which seems OK), but don't know which
one is the
'right' one to use. Any help would be appreciated.
I'd opt for a strategy that didn't lose information, starting maybe
with a survival model approach.
Royal College of Surgeons in Ireland
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