I'm working with a dataset with high attrition rate and am considering using Lee bounds to estimate the treatment effect. Below is the code I am using to determine the share of respondents I need to trim above/below to compute the Lee bounded treatment effect for a binary treatment variable.
Code:
quietly count if intervention==0 & time==0 local tot_control=`r(N)' quietly count if intervention==1 & time==0 local tot_treatment=`r(N)' quietly count if intervention==0 & time==1 & consent2==1 local found_control=`r(N)' quietly count if intervention==1 & time==1 & consent2==1 local found_treatment=`r(N)' local q_control=`found_control'/`tot_control' local q_treatment=`found_treatment'/`tot_treatment' if `q_treatment'>`q_control' { local q1=(`q_treatment'-`q_control')/`q_treatment' } if `q_treatment'<`q_control' { local q1=(`q_control'-`q_treatment')/`q_control' }
Thanks
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