I have data from a study in which male and female doctors each read 6 vignettes describing patient situations. The vignettes vary the age of the patient and also the level of pain the patient is in.
Each doctor reads the same 6 vignettes, and then makes a decision about whether to proceed with surgery or not.
Here is the table of counts
I've also made the raw data available here.
Ultimately what I'm interested in is the impact on the decision to go to surgery of
- Doctor's sex
- Patient pain level
- Patient age
It seems to me that there are some issues with the manipulation that was used, inasmuch as in many of the vignettes it's overwhelming that the doctor calls for surgery. For example, even in the mild pain vignette basically all doctors want surgery all the time, irrespective of whether the patient is old or young.
Under ideal circumstances I had hoped to say something like "There's an association between pain level and proceeding with surgery, but only if the doctor is female" or "there's an association between patient age and the doctor declining surgery, but only if the doctor is male".
It seems unlikely that such a conclusion can be reached from the observed data table, but I would like to do the analysis that could have justified such a conclusion if the results were different.