topic Re: Interrupted time series with proc autoreg in Statistical Procedures

Interrupted time series with proc autoreg

Levi_M — Thu, 23 Jun 2022 14:17:57 GMT

Hi,

After a discussion, I need a little reassurance that my ITS approach for this relatively simplistic model is appropriate. I have observed rates from 1 location over 36 months with an intervention at 24/25 and no control group. Fixed effects so I opted not to use glimmix, however the base model results between the two are identical (if I do not include a random _residual_ or intercept in the mixed model). Below is (1) a base model and (2) an example adjusting for autocorrelation and heteroscedastic variance.

Would appreciate your thoughts,

variables

all_abx_rate = rate

month = 1-36

intervention = 0 or 1

time_aft_int = 1-12 starting at month 25

base:

proc autoreg data=have outest=allabx_param_estmts;

model all_abx_rate = month intervention time_aft_int;

where location=4;

output out=allabx_areg pm=trendhat LCLM=lclm UCLM=uclm p=yhat LCL=lcl UCL=ucl;

run;

adjusted:

proc autoreg data=have outest=allabx_param_estmts;

model all_abx_rate = month intervention time_aft_int /

method=ml nlag=13 backstep dwprob loglikl

garch=(q=1, p=1);

where location=4;

output out=allabx_areg pm=trendhat LCLM=lclm UCLM=uclm p=yhat LCL=lcl UCL=ucl;

run;

Thank you all!!

Re: Interrupted time series with proc autoreg

sbxkoenk — Sat, 25 Jun 2022 09:57:57 GMT

Hello,

Overall, it seems OK to me.

Although I generally do not use this effect in ITS (Interrupted Time Series Regression):

time_aft_int = 1-12 starting at month 25

I usually code the intervention variable itself as :

intervention : always 0 , but a 1-pulse at month 24
intervention : always 0 , but a constant 1 as from month 24 throughout until end-of-series
intervention : always 0 , but a 1 for month 24, a 2 for month 25, a 3 for month 26 and so on ... (allows for trend changes)
other schemas are possible

It all depends on the effect you think your intervention has:

An outlier having effect only on the moment itself.
A structural break in level
A structural break in level and in trend
A structural break in level, trend and variance
...

Re: Interrupted time series with proc autoreg

Levi_M — Mon, 15 Aug 2022 12:33:50 GMT

Hi Koen,

I wanted to revisit your answer with a question:

You mention not using the effect "time_aft_int" in ITS, however, you list it under schemas to "allow for trend changes" and I see it is also reference in the "PROC MODEL" solution paper.

Could you clarify why you would not use it but it is included in references?

Thank you!