Thanks a lot for your advice, Steve! It's extremely helpful.
There's just one point in your response I'm not sure I understand. What do you mean when you write that each child will inherit the probability weight of his/her mother? Do I not need to adjust the weights to account for the fact that the number of children included in the analysis will vary across women? Also, would you agree that, in your first suggested approach, I should keep women without children in the dataset and use the 'subpop' option with the svyset command?
Once again, many thanks for your help.
Alex
________________________________________
From: [email protected] [[email protected]] On Behalf Of Steven Samuels [[email protected]]
Sent: Friday, October 24, 2008 2:21 PM
To: [email protected]
Subject: Re: st: svyset when looking at children of respondents
Alex:
Too start off, each child will inherit the probability weight,
stratum, and cluster assignments of its mother.
I see two ways of accounting for clustering by mother:
1. Add mother as a last stage of "sampling" in your -svyset- command,
but with no finite population correction. See the -svyset- help or
the Stata Survey manual. Use Stata's -svy: logit- command.
2. Fit a multilevel logistic model (level 1: child, level 2: mother)
with -gllamm- (downloadable from SSC, manual http:// www.bepress.com/
ucbbiostat/paper160). -gllamm- accepts probability weights and a
cluster unit above than the highest level in your model. -gllamm- is
not a -svy- enabled program, so you cannot use the stratum
information in the survey design. However you can use stratum-level
covariates. Stas Kolenikov has a demo at http://www.unc.edu/~skolenik/
stata/gllamm-demo.html
If you are interested in conditional, rather than marginal,
predictions, you might choose to ignore the survey sampling weights
altogether.
I recommend the -glamm- option. With -glamm- you will be able to
model woman-level effects as fixed and random.
You should be aware of a potential bias in selecting the births for
your study data. Women may prefer to end their pregnancies with a
successful one (in some places, perhaps, with a successful male
birth). If this is the case, you should exclude a woman's last birth
from your data. To guard against this problem, you may also include
as a covariate the outcomes of prior pregnancies and births. I would
not recommend this if you are interested in marginal, rather than
conditional, prediction. (-gllamm- will do both kinds.)
If you want to use Stata's -svy- commands, and you are combining
multiple surveys, there are other issues. I suggest that you create
"super-strata" which cross countries or survey periods with the
within-survey strata.
Good luck!
-Steve
On Oct 24, 2008, at 12:44 PM, Ergo, Alex wrote:
> Dear A
> I'm working with large population surveys. The individuals
> interviewed are women of
> reproductive age. Among many other things, the respondents provide
> information relating
> to their children. All this information is stored in the
> respondent's record.
> I would like to run some logistic regressions with infant mortality
> as dependent
> variable (1 if child died within the month following birth; 0
> otherwise). In order
> to create this dependent variable, I need to reshape the dataset
> from wide to long
> so as to have one live birth per record. I do not consider all the
> children for
> which information is available, but only those born up to 10 years
> before the
> mother's interview date.
> In this situation, what is the most appropriate approach to account
> for the complex
> survey design? I thought of using the svyset command, but I'm not
> sure how. More
> particularly, should I account for the clustering of live births at
> the level of the
> respondent and for the fact that respondents who did not have any
> live birth in the
> last 10 years are omitted from the regression analysis? If so, how?
> Should I adjust
> the sample weights when more than one child is from the same mother?
> I'm using STATA 9.2.
> I hope someone can help me with this. Thanks in advance!
> Alex
>
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