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Date:         Wed, 9 Feb 2005 12:01:08 -0300
Reply-To:     Hector Maletta <hmaletta@fibertel.com.ar>
Sender:       "SPSSX(r) Discussion" <SPSSX-L@LISTSERV.UGA.EDU>
From:         Hector Maletta <hmaletta@fibertel.com.ar>
Subject:      Time to event
Content-Type: text/plain; charset="us-ascii"

I am trying to estimate interval between births from Bolivian census data about the date of birth of the latest child born from women over 15, and predict the hazard rate of having a new baby (for women of various ages and various numbers of children already born, including childless women) from other variables in the census. Besides ordinary census questions, this census asked every woman over 15 how many children she has given birth to, and the date of birth of the latest one (month and year). So I have the birth order of the latest child, and the interval elapsed between the birth of the latest child and the census date, but not the interval between the births of any two children. For some women the latest is the first, for some the latest is the last, for some is just another one. Some women may still bear another baby at some time after the census, while other women bear no more children in their lives. If I could figure out how to estimate the probability of having a baby so many months or years after the latest child, and considering that I also know the birth order of the latest child, I could potentially estimate the hazard rates for new births and the change in the interval between births according to birth order, mother's age and other variables. To attack this problem I have thought of the following possible strategies: 1. Consider all cases as right-censored, because by definition no other birth has occurred since the latest up to the census date. In other words, all cases are right-censored, and no event (new birth) occurred, but the censored intervals are of different length.I do not know whether you can work with a dataset in which all cases are censored and no event ever occurs. 2. Consider the opposite of giving birth as the event, i.e. the event would be defined as the event of NOT having a baby at each time point after the birth of the latest birth. The event of not having a baby every month or year since their latest child is, of course, observed for all women. Not having a baby is a repeatable event which is repeated every month or year since the latest birth to census date when all cases are censored out. Repeatable events imply some difficulties in time to event models. The data being from a census, cases are aplenty and statistical significance is not a big constraint. Even for a small country like Bolivia, women with a child born in the last 5 years are nearly 800,000, and the total number of women of bearing age is about 2.5 million. I prefer using births in the last 5 years only, to avoid recall errors which are reportedly very frequent with longer recall intervals (i.e. women having had their latest child more than 5 years ago) and also because many potential explanatory variables (like place of residence, marital status, and others) refer to the current status of the women, and may not be applicable to the time of births occurred many years ago. I am not a demographer and have only a limited acquaintance with time-to-event models. I suspect demographers may have a standard strategy for this kind of situation, but somehow I haven't found it so far. I'd like to know how I could model this problem in order to arrive at a solution, possibly using SPSS Cox regression to introduce predictors. Any help appreciated. Hector


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