Hi! I am trying to use Interrupted time series with ARIMA model to compare before and after at intervention=45 data outcome; input outcome time intervention time_af_int; datalines; 9 1 0 0 9 2 0 0 10 3 0 0 8 4 0 0 8 5 0 0 6 6 0 0 6 7 0 0 13 8 0 0 20 9 0 0 23 10 0 0 29 11 0 0 34 12 0 0 19 13 0 0 39 14 0 0 44 15 0 0 29 16 0 0 34 17 0 0 62 18 0 0 50 19 0 0 46 20 0 0 51 21 0 0 36 22 0 0 42 23 0 0 48 24 0 0 30 25 0 0 64 26 0 0 66 27 0 0 77 28 0 0 54 29 0 0 74 30 0 0 48 31 0 0 52 32 0 0 73 33 0 0 77 34 0 0 83 35 0 0 55 36 0 0 48 37 0 0 48 38 0 0 47 39 0 0 44 40 0 0 49 41 0 0 64 42 0 0 35 43 1 1 77 44 1 2 46 45 1 3 58 46 1 4 55 47 1 5 70 48 1 6 41 49 1 7 56 50 1 8 45 51 1 9 57 52 1 10 62 53 1 11 51 54 1 12 76 55 1 13 58 56 1 14 46 57 1 15 71 58 1 16 62 59 1 17 64 60 1 18 59 61 1 19 54 62 1 20 70 63 1 21 54 64 1 22 65 65 1 23 52 66 1 24 56 67 1 25 70 68 1 26 71 69 1 27 70 70 1 28 60 71 1 29 ; run; there are the steps I went through 1 check for stationarity by using PROC ARIMA proc arima data=sample;
identify var=outcome stationarity=(adf);
run; the results showed the outcome is stationarity 2. from ACF PACF plots the AR=2 my questions are 1.how I can estimate the coefficient of the model (b0,b1,b2,b3)with AR=2 if I used the linear regression outcome=b0+b1*time+b2*intervention+b3*time_af_int 2. can I use the nonlinear regression with ARIMA? 3. how account for the seasonality?
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