Hi guys,
I have to run multiple regression time series modelling on seasonal infection data.
These data are: hospitalizations of patients with infections from 3 pathogens across 5 epidemic seasons. I have to model linear trend, secular trend and polynomial trend.
Specifically, what I have to model is the following (pathogens: virus1, virus2, virus3. Totally 3 pathogens):
Tier 2 variables (time trends):
- Linear trend or “βs1t ”
- Seasonal trend or “βs2sin(2πt/52) + βs3cos(2πt/52)”
- Secular polynomial trend or “βs1t + βs2t2+βs3t3”
Tier 3 variables (time lags):
- Time lag (+/- 1 weeks)
- Time lag (+/- 2 weeks)
- Time lag (+/- 3 weeks)
Tier 4 variables (COVID-19 indicator + interactions):
- COVID-19 indicator x Weekly number of virus1 admissions
- COVID-19 indicator x Weekly number of virus2 admissions
- COVID-19 indicator x Weekly number of COVID-19 admissions
- COVID-19 indicator x Weekly number of all other causes admissions
Is there a similar study I can inspire to and available documentation on sas coding/data preparation to deal with this predictions?
Thank you in advance