95% Confidence Interval for relative concentration index

[Jounghee Lee]

Hello

I would like to calculate 95% CI of relative concentration index. However, I could not find a stata command for this. Could anyone kindly share this stata command?

To briefly explain my dataset, it is a complex survey design. After I opened up my dataset, I have used the following stata command.

svyset [pweight=wt_itvex], strata(kstrata) psu(psu)

conindex overw_obese_bi_valid [aweight=wt_itvex], rankvar(mincome_per_capita) bounded limits (0 1) truezero wagstaff cluster (psu) compare(town_t)

** variable information
(overw_obese_bi_valid: binary variable for overweight/obese adults)

(mincome_per_capita: continuous variable for monthly income per capitia variable)

(town_t: categorical variable for urban and rural areas)



After I run this command, I could get index value and standard error, but not 95% CI (You can also see the results in the attached file).


Many thanks in advance.















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[Rich Goldstein]

after using -conindex-, you can type "return list" and see the necessary information that you need to form your own CI's; for some generic help see Maarten Buis' tip: https://journals.sagepub.com/doi/pdf...867X0800700408

[Jounghee Lee]

Thank you so much. After I used -conindex-, I run "return list".

I have the following results.

I would like to get 95% CI of relative concentration index for total population, urban (town_t=1), rural (town_t=2) areas.

Could you kindly explain to calculate 95% CI of relative concentration index?'

Many thanks in advance.

[Tariku Tesfaye]

Dear Jounghee Lee , which one is the 95%CI values in the above output? Because, I face the same problem right now while executing 'conindex'

[Matthew Williams]

Dear Jounghee Lee , which one is the 95%CI values in the above output? Because, I face the same problem right now while executing 'conindex'

Dear Tariku,

You can rely on values of CI and their associated SEs to compute 95% CI. Take CI1 in #3 as an example:
95% CI = [0.84 - 1.96*0.41; 0.84 + 1.96*0.41]

hope this is helpful.