## INLA Code for model used in Bennett et al. Lancet Public Health 2018 ## ## yearc1 - Centred year ## imd.id1, imd.id2, imd.id3 - Indexes for deciles of IMD ## age.id1, age.id2, age.id3 - Indexes for Age group ## year.id1, year.id2 - Indexes for year ## age_imd.id1, age_imd.id2 - Indexes for age group/decile of IMD interaction ## epsilon.id1 - Index for age group/decile of IMD/year # Precision for fixed effects fixed.prec = 0.001 #INLA formula fml <- deaths ~ #global terms f(yearc1, model = "linear", mean.linear = 0, prec.linear = fixed.prec) + # IMD specific intercepts f(imd.id1, model="rw1", hyper = list(prec = list(prior = "loggamma", param = c(1, 0.001)))) + # IMD specific trends f(imd.id2, yearc1 , model="rw1", hyper = list(prec = list(prior = "loggamma", param = c(1, 0.001)))) + # age specific intercepts f(age.id1, model="rw1", hyper = list(prec = list(prior = "loggamma", param = c(1, 0.001)))) + # age specific trends f(age.id2, yearc1 , model="rw1", hyper = list(prec = list(prior = "loggamma", param = c(1, 0.001)))) + # rw over time for each IMD f(year.id1,model="rw1",group=imd.id3,control.group=list(model="exchangeable"), hyper = list(prec = list(prior = "loggamma", param = c(1, 0.001)))) + # rw over time for each age group f(year.id2,model="rw1",group=age.id3,control.group=list(model="exchangeable"), hyper = list(prec = list(prior = "loggamma", param = c(1, 0.001)))) + # interaction betwn IMD and agegrp intercepts f(age_imd.id1, model="iid", hyper = list(prec = list(prior = "loggamma", param = c(1, 0.001)))) + # interaction betwn IMD and agegrp trends f(age_imd.id2, yearc1, model="iid", hyper = list(prec = list(prior = "loggamma", param = c(1, 0.001)))) + # overdispersion terms f(epsilon.id1, model = "iid", hyper = list(prec = list(prior = "loggamma", param = c(1, 0.001)))) ###############################################