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Directly standardized rates with improved confidence interval

distratecasevarpopvarusingfilename[ifexp] [inrange] ,standstrata(stratavars)[by(varlist)popstand(varname)list(varlist)sepby(varlist)format(%fmt)formatn(#)mult(#)level(#)dobsonsaving(filename[,replace])prefix(string)postfix(string)]

Description

distrateestimates directly standardized rates and confidence intervals based on the gamma distribution as proposed by Fay and Feuer (1997). Tiwari, Clegg and Zou (2006) modified the formula of the upper confidence limit showing by simulations that this modified gamma confidence interval performs better than the gamma interval of Fay and Feuer and the other intervals. This method produces valid confidence intervals even when the number of cases is very small.

Data must be in aggregate form, i.e. each record must contain the total number of deaths (or events) and population for each stratum as follows

Age strata death pop----------------------------------------0-44 164 4734645-54 143 8317355-64 202 18610865-74 208 32206575+ 283 362051----------------------------------------

usingfilenamespecifies a file containing standard population weigths, typically stratified by age and optionally by other variables. This file must be sorted by the variable specified instandstrata()

Options

standstrata(stratavars)specifies the variables defining strata across which to average stratum-specific rates. These variables must be present in the study population and in the standard population file. This is most often a unique variable containing age categories.

by(varlist)produces directly standard rates for each group identified by equal values of theby()variables taking on integer or string values.

popstand(varname)specifies the variable in the using file that contains the standard population weights. If not specifieddistrateassumes that it is named aspopvarin the study population.

list(varlist)specifies the variables to be listed.

sepby(varlist)draws a separator line whenevervarlistvalues change.

format(%fmt)specifies the format for variables containing the estimates.

formatn(#)specifies the#of digits for the format of the N(population)variable.

mult(#)specifies the units to be used in reported results. For example, if the mortality rate is 0.00526, specifying mult(1000) it will be reported as 5.26.

dobsondisplays Dobson, Kuulasmaa, Eberle and Scherer confidence limits.

level(#)specifies the confidence level, in percent, for the confidence interval of the adjusted rate; see help level.

saving(filename[,replace])allows to save the estimates in a file.

prefix(string)orpostfix(string)adds a prefix or a suffix to the variable names when the estimates are saved.

Exampleuse "C:\Data\SuffolkCounty.dta", clear collapse (sum) deaths pop,by(cindpov agegr)

distrate deaths pop using year2000st, stand(agegr) by(cindpov) mult(100000)

Further options

distrate deaths pop using year2000st, stand(agegr) by(cindpov) saving(DirectSuffolk,replace) format(%8.2f) mult(100000) level(90) list(rateadj lb_gam ub_gam se_gam)

Downloading ancillary files in one of your

`"`c(adopath)'"'directory you can run this example.

(click to run)

Saved results

distratesaves the following inr():Scalars

r(k)number of groups identified by distinct values of the by() variablesMatrices

r(Nobs)1 x k vector of study populationr(NDeath)1 x k vector of number of eventsr(crude)1 x k vector of crude ratesr(adj)1 x k vector of adjusted ratesr(lb_G)1 x k vector of lower bound of Tiwari adjusted ratesr(ub_G)1 x k vector of upper bound of Tiwari adjusted ratesr(se_gam)1 x k vector of standard error of adjusted ratesr(lb_D)1 x k vector of lower bound of Dobson adjusted ratesr(ub_D)1 x k vector of upper bound of Dobson adjusted rates

AuthorsEnzo Coviello (enzo.coviello@tin.it)

ReferencesFay MP, Feuer EJ. Confidence intervals for directly standardized rates: a method based on the gamma distribution.

Statistics in Medicine1997; 16:791-801.Tiwari RC, Clegg LX, Zou Z. Efficient interval estimation for age-adjusted cancer rates.

Statistical Methods in Medical Research2006; 15: 547-569.Public Health Disparities Geocoding Project Monograph. CASE EXAMPLE: Analysis of all cause mortality rates in Suffolk County, Massachusetts, 1989-1991, by CT poverty strata

Also see