I have run an interrupted time series analysis using GLS regression model in R. My data consists of 48 observations [time 1:48], with the intervention implemented at time 20, but it's effect not anticipated until time 29>. Therefore, I have excluded time 21 to 28 from the analysis (in line with other studies). However, I am struggling to get my head around what this does to the standard intervention effect algebra and wondered if anyone could help?
In a standard segmented regression based ITS analysis the Intervention effect is written as:
intervention effect = B0 + B1T + B2Xt + B3TXt
beta0 is baseline intercept - beta1 is pre-intervention trend - beta2 is change in intercept - beta3 is change in slope
The above does not directly translate to my model and I wondered whether anyone had experience of such/could update?
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