What ANOVA test to use?

I'm doing a study on whether 2 groups of physicians: radiologists and oncologists differ in the volume of their contours. Each group has 3 participating physicians and all physicians contour a specific target (haven't thought of what target yet, but let's use the brain stem as an example).

My initial thought is to use a two way ANOVA, but I'm not sure which ANOVA to use. Do I consider each radiologist a repeated measure in the radiology group (and likewise with oncologists in oncology group)? Is that my only independent variable? Which test will tell me if the variations are due to each patient being different or a significant difference between the groups?

The hypothesis is that Oncologists will tend to contour a larger volume than Radiologists.

Below is an example of what the data table might look like. Numbers are made up, but size of study is true. P1 through P21 are the individual patients/subjects. Values represent volume.

• What are P1 through P21? Some discussion about what a "contour" means will be extremely helpful.
– Dave
Commented Nov 22, 2019 at 15:44
• The Hypothesis to be tested is lacking. Is it "radiologist tend to mark larger volumes then oncologists" or is it "radiologist's volume decision on the same target show lower variance/better reproducibility then oncologist's" or what precisely is the hypothesis or null hypothesis? Commented Nov 22, 2019 at 16:03
• P1 through P21 would be the patients. and a contour can be thought of as the volume the doctor deems as the brain stem. Commented Nov 22, 2019 at 16:05
• The hypothesis is similar to what you said, that the oncologists tend to mark larger volumes than radiologists because of the nature of their work/training. Commented Nov 22, 2019 at 16:06
• How about a random effects model where the volume is a linear model of the physicians tendency to mark large or small volumes and an individual size of each P and a dummy for radiologist? Would a random effects model be within you statistical scope? Commented Nov 22, 2019 at 16:09