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From |
Steven Samuels <sjhsamuels@earthlink.net> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: svyset when looking at children of respondents |

Date |
Sat, 25 Oct 2008 18:26:16 -0400 |

On Oct 25, 2008, at 5:11 PM, Ergo, Alex wrote:

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 theprobability weight of his/her mother? Do I not need to adjust theweights to account for the fact that the number of childrenincluded in the analysis will vary across women?

Also, would you agree that, in your first suggested approach, Ishould keep women without children in the dataset and use the'subpop' option with the svyset command?

Once again, many thanks for your help. Alex

-Steve

________________________________________From: owner-statalist@hsphsun2.harvard.edu [owner-statalist@hsphsun2.harvard.edu] On Behalf Of Steven Samuels[sjhsamuels@earthlink.net]Sent: Friday, October 24, 2008 2:21 PM To: statalist@hsphsun2.harvard.edu 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 * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/* * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/ * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

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**Follow-Ups**:**RE: st: svyset when looking at children of respondents***From:*"Ergo, Alex" <aergo@jhsph.edu>

**References**:**st: svyset when looking at children of respondents***From:*"Ergo, Alex" <aergo@jhsph.edu>

**Re: st: svyset when looking at children of respondents***From:*Steven Samuels <sjhsamuels@earthlink.net>

**RE: st: svyset when looking at children of respondents***From:*"Ergo, Alex" <aergo@jhsph.edu>

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