Posted by
Art Kendall on
Jan 24, 2007; 1:40pm
URL: http://spssx-discussion.165.s1.nabble.com/no-subject-tp1073249p1073256.html
A lot depends on the nature of the problem that you are considering. Do
patients with the condition routinely walk out of the hospital if they
do not have co-morbidities? or Are they still in bed outside the
hospital? etc.
First, do scatter plots of LOS by N_of_Comorbidities with different
colored markers for ambulatory/not ambulatory. (perhaps 4 levels
ambulatory, home bed/assisted, skilled nursing facility, deceased.??)
There are notes interspersed below.
Richard Ristow wrote:
> At 04:27 PM 1/23/2007, Angshu Bhowmik wrote:
>
<snip>
>> 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?
>
> No. That throws away information, and doesn't gain you anything. It
> does NOT simplify the model for analysis, even though it means fewer
> numbers written down.
Very well put.
>
>> <snip>
>
> Well, it may come down to,
> . 5-way by 2-level ANOVA, the grouping variables being presence/absence
> of the five co-morbidity categories, probably suppressing all
> interaction terms.
> . Non-parametric analog of the above
> . Survival-analysis analog of the above, if there is one
>
> Hey, methodologists! Help! Can you see that I'm getting near the edge
> of what I can say confidently?
>
>
In the 5 way ANOVA it will be necessary to ignore (suppress) 5 way,
likely 4 way, and possibly 3 way interactions. You might be able to get
the 2-way.
By ignore I mean pool them into the error(residual) term.
An additional way to look at the data is to use correlations.
You could create 2 additional variables. N_of_comorbidities. And
discharged ambulatory/not ambulatory.
1) Use CORRELATIONS to get the simple (aka zero-order) correlations of
LOS with each of the other variables "ignoring" the other independent
variables.
2) Use PARTIAL CORR to get the partials correlations of LOS with each
of the other variables "eliminating" the 2 additional variables.
put the results in a table with a row for each independent variable a
column for the name of the variable and columns for the zero order and
partial correlations. Of course the first two rows representing the 2
new variables will have n/a for the partial correlation.
Take your results with a grain of salt because your number of cases is
so small.
Art Kendall
Social Research Consultants
Art Kendall
Social Research Consultants