I need to analyze a data-set, with a very messy design, I am not sure how. I will try to make it simple. A new kind of stitches was invented, and is tested vs. 2 old kind of stitches. I will call this: Treatment, control 1 and control 2.
A few patients were selected, needing stitches. Each patient was assigned (by the need, not by random) to one of two stitching techniques. There are others, but only these two were tested. I call this variable "procedure type".
Each patient, needed one stitch or more, up to 5 stitches. The problem is, that those patients in need for more than one stitch, received (sometimes) a mix of different stitches. Meaning, that one patient could have treatment and control 1, and other could have 2 treatment and 2 control 2, etc...
I hope I am not mixing terms here, but my experimental unit is the patient and the observations unit is the stitch within the patient. I have 40 treatment stitches, and 20 of each control, all coming from 25 patients.
The measure being tested, is how many minutes did it take for each stitch until the bleeding stopped. The variable can take values: 0,0.5,1,1.5,2,2.5,...
Clinicians claim that the procedure type, i.e. the technique being used is of no clinical importance and should not have any affect. Thus they think the analysis could ignore this factor.
I wanted to ask you, how would you analyze this data, with and without taking into account the technique. I think it should be some sort of a mixed model or a generalized estimating equations model, but I am not sure to define this design exactly in terms of "nesting", "blocking" and so on, and I would like to also fit a SAS code to model the differences between the means of the 3 different treatments, and I wouldn't mind verifying it with R.
For your convenience, I attach a diagram I made of the design: the blue circles are treatment stitches, the red ones are control 1 stitches, and the green are control 2 stitches. Each yellow rectangle is a patient, and the big brown rectangles are the techniques, which again, I would like to try to fit and to try to ignore the see the outcome of that.