Treatment choice , which model ?

[Ivy]

Hello,

I have 6000 patients with 10 treatment choice.  I would like to see which factors are accociated with the doctor's decision about the treatment.  There are 25 factors total.

I am wondering how this should be modeld , what analysis result should be used.

Thank you very much,

Ivy

[Rick_SAS]

It sounds like the response variable is a categorical variable with 10 levels. You can analyze data like that by using a generalized logistic model.  In SAS you can use PROC LOGISTIC for the analysis.  There is an example of a generlized logit model in the documentation for PROC LOGISTIC, along with an explanation of the output, so copy that example. A main-effects model will look something like

MODEL treatment = x1 x2 x3 ... x25 / link=glogit;

where x1-x25 are the 25 factors.

[Reeza]

You could also consider a discriminant analysis, if you consider each treatment option a group.

You need to factor in the doctor though, there tends to be a bias by provider, not sure how that would be handled. Maybe just as a categorical variable? I would suggest anonymizing the docs names from yourself and until you finalize your results to prevent personal bias.  

[PGStats]

You could investigate decision tree procedures. The easiest is the partition platform in JMP. In SAS/STAT, you should try proc HPSPLIT. The skeleton code would look like

proc hpsplit data=myData;
target treatment / level=nom;
input fact1 fact2 fact3 / level=int; /* List of continuous factors */
input fact4 - fact25 / level=nom; /* List of categorical factors */
output nodestats=myNodes importance=myVars;
run;s 

[Ivy]

Thank you all very much !

I will take a look of these procedures.

Have a nice day !

[ballardw]

You might also have to consider the patient's health insurance as some insurance sources may not pay, or only partially pay, for certain procedures and that can influence a provider's choice.