Two part model for health care costs

[nvcarroll54]

Can anyone provide or direct me to SAS code for two part models in GLM.  I am analyzing cost differences between patients who have experienced a poisoning and those who have not.  There are lots of zeroes in the data and it is skewed. From what I've read, the first part of the model would be a logistic regression and the second would be a regression with a gamma distribution and log link.  I am especially interested in how to combine the results of the two regressions to develop estimates of cost differences between the two groups.

[Reeza]

To get you started see the papers at Lexjansen.com

http://lexjansen.com/search/searchresults.php?q=two%20stage%20model

FYI - This is a good place to start research on any SAS topic 🙂

[Funda_SAS · Accepted solution]

Try using PROC FMM:

Your SAS code should look something like this:

proc fmm data=rowdata;

  model response = age income avgexp / dist=binary;

   model response = age income avgexp / dist=gamma;

   model response = / dist=constant; 

run;

The last MODEL statement specifies a constant distribution with all mass at zero for the zero target group.

To understand PROC FMM and finite mixture models take a look at:

• SGF paper: https://support.sas.com/resources/papers/proceedings12/328-2012.pdf
• PROC FMM documentation: http://support.sas.com/documentation/cdl/en/statug/68162/HTML/default/viewer.htm#statug_fmm_syntax09...

Funda

[SlutskyFan]

So I have a flag for claims > 0 (CLAIM_PRE) and a continuous variable for claims (MEDRX_PRE). It would seem that in a two part model the first modle would be predicting CLAIM_PRE (the separate process for 1'sand 0's) and the next model statement for the positive claims. I am not sure how to set this up in the FMM framework. When I enter the following I get lots of errors about conflicting outcome/model statements.

PROC FMM DATA=WORK.HC_MBR_ANLY_23OCT17;
MODEL MEDRX_PRE = ACTIV_PARTICIP / DIST=BINARY;
MODEL MEDRX_PRE = ACTIV_PARTICIP / DIST=GAMMA;
MODEL CLAIM_PRE = / DIST=CONSTANT;
RUN;

Should the data be structured in some way or the PROC specified so that FMM can handle both the binary model to predict occurance of claims and the conditonal on positive gamma model?  I don't see how the same response variable can be used in each model statement if the entire purpose of two part models is to model two different responses? 

Thanks.

[sasuser2017]

nvcarroll54, were you able to find the code for this?

Thanks

[nvcarroll54]

Nothing simple enough for me to understand and use

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[sasuser2017]

I know what you mean... i've been trying to figure this out for over a month now.

Turns out, it's way easier to do it in Stata, but my dataset is way to large for Stata to handle, so I've had to resort back to SAS.

If your dataset is not very large, try running this in Stata. You have to install command twopm, and it's literally just few lines of code. 

Goodluck,