Posted by
Angshu Bhowmik on
Jan 23, 2007; 9:27pm
URL: http://spssx-discussion.165.s1.nabble.com/no-subject-tp1073249p1073254.html
----- Original Message -----
From: "Richard Ristow"
> This struck me as I wrote with methodological questions about this
> problem.
>
> At 11:59 AM 1/16/2007, Angshu Bhowmik wrote:
>
>>I have data on lengths of hospital stay (LOS, in days) in about 100. There
>>are various co-morbidities: Disease B, Disease C etc which may be present
>>or absent. There are in total 18 co-morbidities, but they could be grouped
>>into 5 groups if that makes it easier to perform a more sensible analysis.
>>
>>I want to find out if any of the co-morbidities are increasing (or
>>decreasing) LOS e.g. Does disease C increase length of stay independently
>>(and if it is possible to find out, by how much)?
>
> I wrote suggestion ANOVA; others wrote suggesting (reasonably) survival
> analysis.
>
> One question that at least I missed: You write "There are various
> co-morbidities: Disease B, Disease C etc which may be present or absent."
> I wrote assuming that patients had exactly one, or at most one, of these.
> Is that so?
I am sorry for not being more clear. The patients may have one or more of
the co-morbidities - not just one.
>
> If you see patients with more than comorbidity, it changes the analysis
> and its complexities. It also makes sample-size requirements more
> stringent. I wrote that 100 patients is reasonable for analyzing
> differences among 5 groups, though not 18. If you have combinations,
> though, you may have many more 'groups', i.e. sets of patients with the
> same sets of diseases. You may have to go to n-way ANOVA (I don't think
> the Survival procedures are good at this), or dummy-variable regression.
>
I see (sort of). I was still struggling a bit with your original
suggestions, but I think I have just about managed to get a grasp of them.
This sounds quite complicated though, and I don't know how to set about it.
I suppose one way to simplify it might be to categorise the lengths of stay
into 3 or 4 groups e.g. very short (0) , short (1), long (2) and extra-long
(3) or something like that and then use ordinal multinomial logistic
regression (if I am right). Would this be an acceptable way to do it? At the
end of the day, my aim is just to find out if one or more of the
comorbidities affect length of stay -- the problem is that when there are so
many possible combinations, then it is difficult to isolate the effects of
just one of the comorbidities at a time.
Many thanks to all of your for your valuable suggestions. This is helping me
to get an understanding of the principles involved. I have not yet tried the
survival analysis, but will attempt this over the weekend.
Thanks again,
Angshu