Re: st: R: death rate calculation - (flag: Stata 9/2 SE)

[Rajaram Subramanian Potty <rajara999@gmail.com>]

Dear Samuels,

Thanks for the information. But we have asked only the age for the
people who are surviving at the time of the census which is conducted
in the year 2009 and not the date of birth. This means that we don't
have date of birth information particularly for the children. For dead
people we have collected information on month and year of death. We
also do not have information on information on people who left the
household from 1 January 2006 for other reasons (in other words we
don't have information on migration of usual residents in the HH).
Presently, we have the following information in the data set.

Age of all the usual residents who are alive at the time of census
(census was conducted in the selected areas in the year 2009).
Date and month of interview
Month and year of death of all usual residents since 1, January 2006.
Age at death for all persons those who had died during the reference period.

I am not sure with the above information, whether I will be able to
compute crude death rate using STATA.

Thanks and regards,

RAM

On Sun, Oct 31, 2010 at 12:39 AM, Steven Samuels <sjsamuels@gmail.com> wrote:
> --
> Here are some more illustrations for computing rates with -poisson- as well
> as -ratio-. One can argue that, because separate reports were made for each
> household, CIs should be based on HH variation.  So, I've included an
> example of that.
>
>
> Steve
>
> Steven J. Samuels
> sjsamuels@gmail.com
> 18 Cantine's Island
> Saugerties NY 12477
> USA
> Voice: 845-246-0774
> Fax:    206-202-4783
>
> ******************************************************
> sysuse auto, clear
> rename foreign death
> gen exp1000 =mpg/1000
> recode rep78 1/2=3
>
>
> /* Overall Rates */
> ratio death/exp1000
> bootstrap, reps(100): ratio death/exp1000
>
> quietly poisson death, exposure(exp1000)
> nlcom exp(_b[_cons]) //CI based on the Poisson Assumption
>
> quietly poisson death, exposure(exp1000) robust
> nlcom exp(_b[_cons]) //CI based on robust SE
>
> gen household = int(_n/5)  //artificial HH cluster variable
>
> quietly poisson death, exposure(exp1000) vce(cluster household)
> nlcom exp(_b[_cons]) //CI based on hh variation
>
>
> /* Subgroup computations */
> total death, over(rep78)
>
> bootstrap, reps(100): ratio death/exp1000, over(rep78)
> estat bootstrap    //better CIs
>
> levelsof rep78, local(lv)
> foreach i of local lv {
> di "rep78 = `i'"
> quietly poisson death if rep78==`i', exposure(exp1000) robust
> nlcom exp(_b[_cons]) //CI based on robust SE
> }
> ******************************************************
>
>
>
>
>
>
>> RAM:
>> I thought that's what you meant, but I'm still a little confused. If you
>> have  complete counts of people and events between 2006 and 2009, how did
>> you use external data?  Ignoring external data, I assume you have the
>> following variables, or something like them:
>>
>> date_enter   // date entered into observation
>>        •Jan 1 2006 individuals living in the HH in Jan 2006
>>        • Month of entry to the HH for individuals who were not living in
>> the HH in Jan 1 2006 ( month of birth for children)
>> date_exit   //date observation ended
>>        • Date of interview for persons alive at interview
>>        • Month of death for deaths
>>        • Month of exit for those who left the HH for other reasons
>>
>> death ( indicator for end point)
>>        = 1 for those who died
>>        = 0 for those alive at the date that observation ended
>>
>> Note: because you have only month of deaths and of some entries and exits,
>> there will be measurement error. I suggest that you assign day of month
>> either as the 15-th or assign it randomly to a number between 1 & the number
>> of days. Using the 15-th will reduce the maximum error to ± 1 month. Also,
>> if you want age-specific death rates, , then some people will cross an
>> age-group boundary during the course of follow-up. You would have to split
>> the observation time for such people between age groups. See -stset- and
>> -stsplit-.
>>
>> *********************************************
>> gen exposure = (date_enter - date_exit)
>> **********************************************
>> Comment: There are two situations in which these dates and exposure times
>> will be problematic: 1) deaths in the first month of observation; and 2)
>> infant deaths in the first month of life.
>>
>> To get deaths per 1,000 person years,
>> ***************************************
>> gen exp1000 = exposure/(1000*365.25)
>> **************************************
>> ratio death/exp1000
>> ratio death/exp1000, over(age_gp gender)
>> ****************************************
>>
>> Many investigators put confidence intervals around rates computed from
>> complete data. They consider that the rates display "natural variability" (
>> http://stat-www.berkeley.edu/~brill/Papers/biometrics.pdf).  I agree with
>> this approach.  To get better CIs in Stata 9 I would use:
>> **************************************
>> bootstrap, reps(1000):  ratio death/exp1000
>> ****************************************
>>
>> For modeling, try -poisson- or one of Stata's other count commands.
>>
>> Regards,
>>
>> Steve
>>
>> Steven J. Samuels
>> sjsamuels@gmail.com
>> 18 Cantine's Island
>> Saugerties NY 12477
>> USA
>> Voice: 845-246-0774
>> Fax:    206-202-4783
>>
>
> On Fri, Oct 29, 2010 at 4:15 AM, Steven Samuels <sjsamuels@gmail.com> wrote:
>>
>> -
>> You recently asked for assistance with a sample survey, but you say
>> nothing
>> about a sample in this thread. Since you used the word "census" (which
>> means
>> an attempted 100% count),  may we assume that you have observations from
>> all
>> the households in the study population?
>>
>> Steve
>>
>>
>> On Oct 28, 2010, at 7:38 AM, Rajaram Subramanian Potty wrote:
>>
>> Dear All,
>> But my data set is not in the form to do a event history analysis.  I
>> have the details of all the usual residents in the household and
>> collected information on age, sex and other paritculars of the persons
>> present (surviving) at the time of survey. And for all the person who
>> dead after the reference period, i.e. after 2006, we have collected
>> age at death, sex of the person, month of death and year of death.
>> From this information, I want to calculate the death rate.
>>
>> Is any one know how my data can be converted to do the analysis that
>> is suggested by Carlo?
>>
>> Thanks and regards,
>>
>> RAM
>> On Thu, Oct 28, 2010 at 2:39 PM, Carlo Lazzaro <carlo.lazzaro@tin.it>
>> wrote:
>>>
>>> Dera Rajaram,
>>>
>>> - help stptime -
>>>
>>> can light the way.
>>>
>>> Kind Regards,
>>> Carlo
>>> -----Messaggio originale-----
>>> Da: owner-statalist@hsphsun2.harvard.edu
>>> [mailto:owner-statalist@hsphsun2.harvard.edu] Per conto di Rajaram
>>> Subramanian Potty
>>> Inviato: giovedì 28 ottobre 2010 7.33
>>> A: statalist@hsphsun2.harvard.edu
>>> Oggetto: st: death rate calculation
>>>
>>> Dear All,
>>>
>>> I would like to calculate the death rate from a Household Census
>>> conducted in the selected areas of a district. In the household we
>>> have listed information on all the usual members in the household and
>>> the number of usual residents died since January 2006. The census was
>>> carried out in the year 2009. I just want to know how to calculate the
>>> death rate using the stata. Presently, I am calculating the death rate
>>> using excel after obtaining the total usual resident deaths during the
>>> reference period and the total usual resident population (converting
>>> the population enumerated into the person years lived during the
>>> reference period using the population growth in the district).
>>>
>>> Thanks and regards,
>>>
>>> RAM
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