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Re: Timing of variables' collection [message #25709 is a reply to message #25700] Tue, 29 November 2022 08:19 Go to previous messageGo to previous message
Bridgette-DHS is currently offline  Bridgette-DHS
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Registered: February 2013
Senior Member

Following is a response from Senior DHS staff member, Tom Pullum:

We often use models in which the temporal sequencing of the variables is inconsistent with causality. I think it's important to be aware of that and say something about it in whatever you write up. The usual justification is that many characteristics don't change much over time, so a value that is too old or too recent can be used as a proxy for the value at the time when you would like to have it. Type of place of residence and occupation are examples. You can think of the difference between the measured value and the "true" value as measurement error that will dilute or attenuate the association. There are some sophisticated methods to adjust for such things, but (personally) I think there are so many other kinds of measurement error in the data that those methods would just give a false sense of confidence in the results. This is a philosophical issue. When the variables are out of sequence, I try to interpret the results in terms of association rather than causation.

I think m57a-x is the set of variables on place of antenatal care that you are looking for. This is a multiple option type of variable--more than one option can be selected. Some options in the standard set are NA.
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