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st: Combining m & f gamma confidence intervals to generate persons gamma confidence intervals using -distrate-


From   Tim Evans <Tim.Evans@wmciu.nhs.uk>
To   "'statalist@hsphsun2.harvard.edu'" <statalist@hsphsun2.harvard.edu>
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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