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Re: st: Re: Re: RE: weight and easier way
2007/7/12, Michael Blasnik <[email protected]>:
...
Woops, typo on last line -- replace it with:
gen corrector=N_dpto_el/(proyection*N_dpto_agegp_el)
Michael
----- Original Message -----
From: "Michael Blasnik" <[email protected]>
To: <[email protected]>
Sent: Thursday, July 12, 2007 7:59 AM
Subject: st: Re: RE: weight and easier way
> ...
> I'm not sure exactly what you are doing, but it doesn't seem like you need a
> loop at all, or even many commands.
>
> 1) Create the agegp variable and save the master dataset.
>
> 2) Create a dataset with the "proyection" constants by department and gender.
> It should have three variables: dpto, el, and proyection. Sort it by dpto el
> before saving it as proyection.dta
My excel dataset (proyections) is:
gp Total Men Women
0 10 5 5
1-4 12 4 8
5-9 20 3 17
...................................
95+ 3 0 3
My stata dataset (microsurvey) is:
dpto year_weight e1 e2
1 123 1 13
1 89 1 65
2 54 2 25
...................................
19 152 2 0
19 58 2 39
Where dpto is state, year_weight is annual weight, e1 is 1 if man and
0 if woman, e2 is age and others variables.
Weights are wrong so I want to correct using population proyections
according dpto, sex and age.
I would like to compute a new corrected weight without dissmining observations.
Thanks,
Sebastián.
>
> Then:
>
> use masterdata
> bysort dpto agegp el: gen N_dpto_agegp_el=_N
> bysort dpto el: gen N_dpto_el=_N
> merge dpto el using proyection, nokeep
> gen corrector=N_dpto/(proyection*N_dpto_agegp_el)
Why don't include e2 or agegp? Is el equals e1?
nokeep means that I drop observations?
>
>
> Michael Blasnik
>
> ----- Original Message -----
> From: "Sebastian Kruk" <[email protected]>
> To: <[email protected]>
> Sent: Thursday, July 12, 2007 7:39 AM
> Subject: st: RE: weight and easier way
>
>
>> Hi dear statalist users,
>>
>> I have been in vacation but I work anyway.
>>
>> Do you remember my problem?
>>
>> I have a households survey and population proyections.
>>
>> All the weights are wrong.
>>
>> Some of my varriables are:
>>
> <snip>
>> Weights in microsurvey are wrong, It must be corrected by new one
>> using population proyections.
>>
>> I do the next but I have problems using a loop.
>>
>> *Make a categorical variable for group of age:
>>
>> egen agegp=cut(e2), at
>> (0,1,5,10,15,20,25,30,35,40,45,50,55,60,65,70,75,80,85,90,95,100)
>>
>> *Put labels
>>
>> label define agegp 0 "0" 1 "1-4" 5 "5-9" 10 "10-14" 15 "15-19" 20
>> "20-25" 25 "25-29" 30 "30-34" 35 "35-39" 40 "40-44" 45 "45-49" 50
>> "50-54" 55 "55-59" 60 "60-64" 65 "65-69" 70 "70-74" 75 "75-79" 80
>> "80-84" 85 "85-89" 90 "90-94" 95 "95+"
>>
>> *Compute number of men by group of age and departamento (means state in
>> English)
>>
>> egen n_h_0=total(agegp==0 & e1==1), by (dpto)
>> egen n_h_1=total(agegp==1 & e1==1), by (dpto)
> <snip>
>> egen n_h_95=total(agegp==95 & e1==1), by (dpto)
>>
>> *Computo total men by departemanto
>> egen h_dpto=rowtotal(n_h_*)
>>
>> *Repit for women
>> egen n_m_0= total(agegp==0 & e1=!1), by (dpto)
>> …………………………………………………..
>> egen n_m_95=total(agegp==95 & e1=!1), by (dpto)
>> egen m_dpto=rowtotal(n_m_*)
>>
>> *Make a constan equals men's proyection by departamento
>>
>> gen h_1_p=643547
>> gen h_2_p=
>> …………………..
>> gen h_19_p=
>>
>> *Repet for women
>> gen m_1_p=
>> gen m_2_p=
>> …………………..
>> gen m_19_p=
>>
>> *Compute annual men expansor by departemanto
>> gen corrector=h_dpto/(h_1_p*n_h_0) if e1==1 & agegp==0
>> replace corrector=h_dpto/(h_1_p*n_h_1) if e1==1 & agegp==1
> <snip>
>> replace corrector=h_dpto/(h_1_p*n_h_95) if e1==1 & agegp==95
>>
>> *Repet for women
>> replace corrector=h_dpto/(h_1_p*n_h_0) if e1==1
>>
>> Bye,
>>
>> Sebastian.
>
> *
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*
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*
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* http://www.ats.ucla.edu/stat/stata/