Dear all,
thanks in advance for your precious time.
I have to solve an ordered regression problem.
I have 5 groups of patients, treated with 5 different drug doses.
Subjects were measured with an ordinal efficacy outcome (variable "v") ranging from 0 to 5.
The outcome was measured at 4 different timepoints ("time" variable): 30, 60, 120 and 180 minutes.
My model looks like this:
meologit v i.dose##i.time|| id:, or
The problem lies in the fact that I would like to compare the 5 doses with each other in terms of effectiveness over time.
If I do:
margins i.dose#i.time, pwcompare(pveffects) mcompare(bonferroni) atmeans
I would get pairwise comparisons for any dose-drug combination but.....for any possible level of outcome! And that's too many comparisons and difficult to report.
How can I make an "overall" comparison of doses over time, without having comparisons for each level of outcome?
thanks in advance for your precious time.
I have to solve an ordered regression problem.
I have 5 groups of patients, treated with 5 different drug doses.
Subjects were measured with an ordinal efficacy outcome (variable "v") ranging from 0 to 5.
The outcome was measured at 4 different timepoints ("time" variable): 30, 60, 120 and 180 minutes.
My model looks like this:
meologit v i.dose##i.time|| id:, or
The problem lies in the fact that I would like to compare the 5 doses with each other in terms of effectiveness over time.
If I do:
margins i.dose#i.time, pwcompare(pveffects) mcompare(bonferroni) atmeans
I would get pairwise comparisons for any dose-drug combination but.....for any possible level of outcome! And that's too many comparisons and difficult to report.
How can I make an "overall" comparison of doses over time, without having comparisons for each level of outcome?
Code:
* Example generated by -dataex-. For more info, type help dataex clear input byte dose int time byte v float id 0 30 4 1 0 30 5 2 0 30 5 3 0 30 4 4 0 30 4 5 0 30 3 6 0 30 4 7 0 30 5 8 1 30 4 9 1 30 3 10 1 30 5 11 1 30 4 12 1 30 4 13 1 30 4 14 1 30 4 15 1 30 5 16 2 30 2 17 2 30 2 18 2 30 2 19 2 30 3 20 2 30 2 21 2 30 2 22 2 30 1 23 2 30 2 24 3 30 0 25 3 30 0 26 3 30 1 27 3 30 1 28 3 30 1 29 3 30 0 30 3 30 0 31 3 30 1 32 4 30 1 33 4 30 0 34 4 30 1 35 4 30 2 36 4 30 0 37 4 30 0 38 4 30 0 39 4 30 0 40 0 60 5 1 0 60 5 2 0 60 5 3 0 60 4 4 0 60 5 5 0 60 4 6 0 60 5 7 0 60 5 8 1 60 5 9 1 60 5 10 1 60 4 11 1 60 5 12 1 60 4 13 1 60 5 14 1 60 5 15 1 60 5 16 2 60 2 17 2 60 3 18 2 60 3 19 2 60 4 20 2 60 3 21 2 60 3 22 2 60 3 23 2 60 3 24 3 60 2 25 3 60 1 26 3 60 1 27 3 60 1 28 3 60 0 29 3 60 1 30 3 60 1 31 3 60 2 32 4 60 1 33 4 60 1 34 4 60 1 35 4 60 1 36 4 60 1 37 4 60 1 38 4 60 1 39 4 60 2 40 0 120 5 1 0 120 5 2 0 120 5 3 0 120 4 4 0 120 5 5 0 120 5 6 0 120 5 7 0 120 5 8 1 120 5 9 1 120 5 10 1 120 5 11 1 120 5 12 1 120 4 13 1 120 5 14 1 120 5 15 1 120 4 16 2 120 5 17 2 120 5 18 2 120 5 19 2 120 4 20 end
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