I am really struggling with this issue and hope someone can help.
I have a generalized estimating equation model based on matched pairs (1:3) /clusters. The model is simply the relationship of cost to disease_status (binary variable). I would like an estimate of the change in cost by disease status. The clusters have a pair ID. My goal is to bootstrap the model sampling from clusters and use the margin results to estimate the 95% CI using the percentile method. My code is as follows:
(I have many costs so I used a program - this is just a demonstration of it on one cost)
Code:
capture program drop dydx_margins program define dydx_margins, eclass xtgee cost i.disease_status fam(gamma) link(log) corr(independent) i(pairid2) margins, dydx(disease_status) post exit end xtset, clear bootsstrap _b, reps(1000) seed(1234) cluster(pairid) idcluster(pairid2): dydx_margins
Someone recently asked me to make sure that different cluster IDs were given to replications of the same cluster. This was to make sure I was not overweighting the case-control differences from those clusters which may have been selected more than once. I thought I fixed this by specifying the idcluster command and making sure I told xtset to clear and refer to that new pair variable in the xtgee.
But to check I ran this code below just removing the idcluster command:
Code:
capture program drop dydx_margins2 program define dydx_margins2, eclass xtgee cost i.disease_status fam(gamma) link(log) corr(independent) i(pairid) margins, dydx(disease_status) post exit end xtset, clear bootstrap _b, reps(1000) seed(1234) cluster(pairid): dydx_margins2
Thanks!
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