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age at the first birth [message #9368] Mon, 21 March 2016 06:53 Go to next message
zakzok is currently offline  zakzok
Messages: 10
Registered: March 2016
Location: Vienna
Dear sir

want to find the age at the first and second birth by stat and I used this formula by STAT but I don't get the same result in DHS 2014 (EGYPT).

gen afb1=int((b3_01-v011)/12)
tab afb1,m
tab afb1 [iweight=v005/1000000],m

my result
afb1 Freq. Percent Cum.

13 .515313 0.00 0.00
14 11.377062 0.05 0.05
15 18.963472 0.09 0.14
16 82.596987 0.38 0.52
17 149.479107 0.69 1.21
18 272.675723 1.25 2.46
19 486.101112 2.23 4.69
20 622.325106 2.86 7.55
21 868.731214 3.99 11.55
22 1,022.3924 4.70 16.24
23 1,210.3369 5.56 21.81
24 1,300.304 5.98 27.78
25 1,345.6182 6.18 33.96
26 1,403.8393 6.45 40.42
27 1,352.4216 6.21 46.63
28 1,312.5941 6.03 52.66
29 1,250.5567 5.75 58.41
30 1,217.9228 5.60 64.00
31 1,003.9966 4.61 68.62
32 1,021.2922 4.69 73.31
33 779.58984 3.58 76.89
34 680.641099 3.13 80.02
35 633.176881 2.91 82.93
36 514.568482 2.36 85.30
37 433.137207 1.99 87.29
38 293.818318 1.35 88.64
39 200.703208 0.92 89.56
40 157.927663 0.73 90.28
41 92.040127 0.42 90.71
42 70.489689 0.32 91.03
43 34.743824 0.16 91.19
44 14.816131 0.07 91.26
45 14.898599 0.07 91.33
46 6.167603 0.03 91.36
47 1.103819 0.01 91.36
. 1,880.1391 8.64 100.00

Total 21,762.002 100.00

what's the problem?

thank you in advance
Re: age at the first birth [message #9526 is a reply to message #9368] Fri, 08 April 2016 12:52 Go to previous messageGo to next message
Bridgette-DHS is currently offline  Bridgette-DHS
Messages: 2280
Registered: February 2013
Senior Member
Dear User,

A team member is working on your request, and we will get back to you soonest.

Re: age at the first birth [message #9551 is a reply to message #9526] Wed, 13 April 2016 08:58 Go to previous message
Bridgette-DHS is currently offline  Bridgette-DHS
Messages: 2280
Registered: February 2013
Senior Member
Following is a response from Senior DHS Stata Specialist, Tom Pullum:

The difficulty with tables 7.4 and 7.5 is due to the fact that only ever-married women (EMW) were eligible for the women's interview in this survey. Therefore information about age at marriage is only available for women who are married. To describe age at marriage in the population of all women, you need to know how many women at each age are never-married. You might try to fill in those women by combining the IR and PR files, but that is not how DHS does it. (Actually I have tried to match the tables this way, and I think that's a legitimate strategy, but it will not give a match.) Instead, to calculate tables 7.4 and 7.5, DHS inflates the EMW sample with the all-woman factors (generically, "awfact"). The cases that are artificially added into the sample this way are considered to be never-married. I emphasize that this is very artificial. These are not real cases. The following Stata lines will produce everything in table 7.4 except for the median age at first marriage. Note that the inflation factor here is awfactt. The final "t" is for total. If you wanted to get this table separately for urban/rural women, for example, you would use awfactu. In table 7.5, the successive panels use awfactu, awfactr, awfacte, and awfactw.

use e:\DHS\DHS_data\IR_files\EGIR61FL.dta, clear
keep v001 v002 v003 v005 v012 v013 v511 awfactt

save e:\DHS\DHS_data\scratch\temp.dta, replace
gen weight=v005
gen never_married=0

save e:\DHS\DHS_data\scratch\emw_temp.dta, replace
use e:\DHS\DHS_data\scratch\temp.dta, clear

gen weight=round(v005*((awfactt/100)-1))
gen never_married=100
replace v511=50

append using e:\DHS\DHS_data\scratch\emw_temp.dta

tab v013 [iweight=weight/1000000]

format never_married %5.1f
tab v013 [iweight=weight], summarize(never_married) means noobs

gen before_15=0
replace before_15=100 if v511<15

gen before_18=0
replace before_18=100 if v511<18

gen before_20=0
replace before_20=100 if v511<20

gen before_22=0
replace before_22=100 if v511<22

gen before_25=0
replace before_25=100 if v511<25

format before* %5.1f
tab v013 if v012>=15 [iweight=weight], summarize(before_15) means noobs
tab v013 if v012>=18 [iweight=weight], summarize(before_18) means noobs
tab v013 if v012>=20 [iweight=weight], summarize(before_20) means noobs
tab v013 if v012>=22 [iweight=weight], summarize(before_22) means noobs
tab v013 if v012>=25 [iweight=weight], summarize(before_25) means noobs

mean before* never_married if v012>=25 [iweight=weight]

Getting the medians in the last column of table 7.4 is also a little complicated, because in Stata a median is always a value that actually occurs in the data. Stata would not give a median age of 21.3, for example, unless 21.3 was actually an age at marriage in the data. Instead, Stata would only give values such as 20, 21, 22, etc. Note also that a median age such as 21.3 implies that age is on a continuous scale, rather than being defined only at integer values.

A second complication with the calculation of the medians in table 7.4 is in the interpretation of, say, age at marriage = 20. It is DHS practice to replace the 20 with 21.0, which is exact age 21, that is, the 21st birthday. That is, continue the program with these lines:

gen v511r=v511+1
replace v511r=. if v511>v012

Then, to get the median age at marriage for women age 25-29 (that is, with v013=3), you do this line:

tab v511r [iweight=weight/1000000] if v013==3,m

Looking at the cumulative percentages in this one-way table, you see a cumulative percentage of 47.48% at v511r=21 and a cumulative percentage of 57.39% at v511r=22. Using linear interpolation between 21 and 22, you would get 50% at age 21.254289, i.e. at 21.3. That's the source of the 21.3 for age group 25-29 in the last column of table 7.4. Similarly for the other age intervals in table 7.4, and similarly for all the medians in table 7.5, but using the appropriate versions of awfact for the covariates as described above.

Of course, all of the calculations of medians could be automated in Stata, but here I'm just showing the basic steps.

I will add that I am personally not comfortable with the line "gen v511r=v511+1". Instead of adding 1, I would probably add .5, thinking of marriage at age 20 at last birthday, for example, as "on the average" marriage at exact age 20.5. However, this is just a matter of interpretation. Any inferences about trends or differentials would be unaffected by whether you add 1 or .5.

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