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Date:   Fri, 26 Aug 2011 13:38:51 -0400
Reply-To:   Sophia Tong <sophiDT@HOTMAIL.COM>
Sender:   "SAS(r) Discussion" <SAS-L@LISTSERV.UGA.EDU>
From:   Sophia Tong <sophiDT@HOTMAIL.COM>
Subject:   time series modeling

Dear listers,

I am new to time series modeling, got a time series project and found the challenge and hope to get help from the list.

I have a 60 months time series data, with dependent variable as monthly prescription drug use rate, and independent variable is month. I am trying to model if certain drug policy change alters the drug prescription rate. Here is the model I am trying to use based on self study:

PROC AUTOREG DATA=Policy; MODEL DRUGRATE=MONTH PA PST_PA/METHOD=ML NLAG=3; TEST MONTH + PST_PA=0; RUN;

Here PA is the policy indicator: 0= before policy period, 1=after policy PST_PA is the months after policy implemented coded as 1,2,3...

The challenge to me is how to choose appropriate nlag= and method=. It changes estimates greatly. according to SAS doc, it seemed nlag=13 and method=yw (defualt) is appropriate, but the publications I can find use nlag=1 and method=ml. Is there a rule of thumb? What are the important numbers (ie. MSE, AIC, total-R square, or something else?) to look as to make judgement of best fitting model?

Any input will be greatly appreciated.

Sophia


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