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st: Combining m & f gamma confidence intervals to generate persons gamma confidence intervals using -distrate-
From
Tim Evans <[email protected]>
To
"'[email protected]'" <[email protected]>
Subject
st: Combining m & f gamma confidence intervals to generate persons gamma confidence intervals using -distrate-
Date
Thu, 24 May 2012 09:57:40 +0100
Hi,
I'm using -distrate- (which) is a user written package) in Stata 11.2 for the purpose of calculating age standardised incidence rates and confidence intervals using the gamma method. I first calculate male and then female rates and CIs. What I want to do is combine the rates and confidence intervals in order to obtain age-sex standardised person rates. However, I'm a little unsure that I am generating the persons (gamma) LCI and UCI correctly. My code is below and any tips would be appreciated - let me know if more information is needed.
* LOAD FEMALE DATA (INCIDENCE OR MORTALITY NUMBERS & POPULATIONS FOR AREAS OF INTEREST)
use "female_data_1.dta", clear
sort age_grp
* CALCULATE RATES WITH DISTRATE
distrate count f_pop using "europopfull.dta", stand(age_grp) mult(100000) saving(dist_f_1.dta, replace)
use dist_f_1.dta, clear
foreach var of varlist count - ub_dob {
rename `var' `var'_f
}
save "dist_f_1.dta", replace
* LOAD MALE DATA (INCIDENCE OR MORTALITY NUMBERS & POPULATIONS FOR AREAS OF INTEREST)
use "male_data_1.dta", clear
sort age_grp
* CALCULATE RATES WITH DISTRATE
distrate count m_pop using "europopfull.dta", stand(age_grp) mult(100000) saving(dist_m_1.dta, replace)
use dist_m_1.dta, clear
foreach var of varlist count - ub_dob {
rename `var' `var'_m
}
*MERGE WITH FEMALE RESULTS
merge using "dist_f_1.dta"
*PERSONS
gen rateadj_p = 0.5*(rateadj_f+rateadj_m)
gen Leffse = 0.5*sqrt(((rateadj_f-lb_f)/1.96)^2 + ((rateadj_m-lb_m)/1.96)^2)
gen lb_p = rateadj_p - 1.96*Leffse
gen Ueffse = 0.5*sqrt(((ub_f-rateadj_f)/1.96)^2 + ((ub_m-rateadj_m)/1.96)^2)
gen ub_p= rateadj_p + 1.96*Ueffse
or should it be:
something like:
gen pGLCI = rateadj_p -(0/2)*sqrt(((rateadj_m - lb_gam_m)/0)^2 + ((rateadj_f - lb_gam_f)/0)^2)
gen pGUCI = rateadj_p +(0/2)*sqrt((lb_gam_m - rateadj_m)/0)^2+((lb_gam_f - rateadj_f)/0)^2)
Best wishes
Tim
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