Hi everybody,

I would like to calculate the adjusted prevalence of smoking (0=non smoker, 1=current smoker) in a repeated cross-sectional study using poisson regression adjusting for age (0=aged 20-49, 1=aged 50-74), gender (0=women, 1=men) and survey year (1=2008, 2=2009, ... 10=2018). I would also like to graphycally display these adjusted prevalence by gender and age in interaction with survey period (1=2008-2011, 2=2012-2015, et 3=2016-2018). To do so I am using margins and marginsplot:

Code:
Code:
glm smoking i.age_cat i.gender#i.survey_period c.survey_year, family(poisson) link(log) vce(robust) eform

margins gender, expression(predict()*100) at(survey=(1(1)3)) vce(uncond)

marginsplot, recastci(rarea)
My question is: can I trust my estimates if I use both survey_year and survey_period in my model, or I should rather use only one of the two such as for example:

Code:
glm smoking ib0.age_cat ib1.gender##i.survey_period, family(poisson) link(log) vce(robust) eform
Thank you in advance for your help,

Giovanni