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From |
Steve Samuels <[email protected]> |

To |
[email protected] |

Subject |
Re: st: Calculating confidence intervals for the ratio of stratified standardised mortality rates |

Date |
Fri, 8 Nov 2013 20:32:47 -0500 |

Here's the Mata version after all. It requires only two -dstdize- calls and will produce the rate ratio and CI for any number of categories. ************************************ forvalues i = 1/2 { dstdize ... by(all_data) using(), /// if time==`i' mata: a`i' = st_matrix("r(adj)") mata: s`i' = st_matrix("r(se)") } mata: ratio = a1:/a2 lr = log(ratio) slr = /// sqrt((s1:/a1):*(s1:/a1) +(s2:/a2):*(s2:/a2)) z = /// -invnormal((100 -st_numscalar("c(level)"))/200) lower = exp(lr - z:*slr) upper = exp(lr + z:*slr) d=(ratio \ lower \ upper)' end clear getmata (ratio lower upper) = d gen nstate=_n do nlabel // redo label define label values nstate nstate format ratio lower upper %8.3f list nstate ratio lower upper save results, replace *********************************. > The proper term for your rates are "directly standardized rates" > "Stratified" is implied and also applies to indirect standardization. > > Your question isn't quite clear, but I assume that you mean that you > want a comparison of the two time periods for each category of > "all_data". Here is code for a single category of all_data. You can > get results for all categories with a -foreach- or -forvalues- loop. > > ****************************************** > dstdize ... if all_data==1, by(time) using... > > matrix a = r(adj) > matrix s = r(se) > scalar ratio = a[1,1]/a[1,2] > scalar slr = > sqrt((s[1,1]/a[1,1])^2 + (s[1,2]/a[1,2])^2) > scalar bound = > -slr*invnorm((1 -c(level)/100)/2) > scalar upper = exp(log(ratio) + bound) > scalar lower = exp(log(ratio) -bound) > scalar list ratio lower upper > ****************************************** > > The formula for the log scale SE (slr) is based on the large sample > result that for an estimate R the delta method estimate of variance is: > > var (log W)≈ var(W)/W > > The formula applies to each component of the log ratio, since they are > independent. > > log ratio = log(adj rate 1) - log(adj rate 2) > > I also have a Mata-based solution that is likely faster if you have a > lot of all_data categories and that puts the results into a data set. > It's a bit too long to list here. If you'd like to see it, join > stackoverflow.com and ask your question in the Stata area > http://stackoverflow.com/questions/tagged/stata. > > Steve > On Nov 7, 2013, at 9:08 AM, Paul Mee wrote: > > All > > Apologies if this is a rather naive question but I hope someone can help me. > > I have been calculating age/sex standardised mortality rates stratified by geographical areas I used dstdize for this in stata and it worked fine and gave me the standardised rates and importantly confidence intervals which I extracted from the relevant macros/matrices . For reference this is the command I used > > dstdize total_hiv_tb_death population adj_cat, by(all_data) /// > using("C:\work\Research\Analysis\Paper1_mortality\stata\rates\std_pop_09_10.dta") level(90) > > No I need to calculate the ratio between the standardised mortality rates in two time periods (i.e. from different separate dstdize commands ) and calculate confidence intervals for these mortality rate ratios . > > Any help with how to do this in stata would be very much appreciated. > > Paul > > [email protected] > > * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/faqs/resources/statalist-faq/ * http://www.ats.ucla.edu/stat/stata/

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