I don't know how much help this would be statistically, or
scientifically, but in such cases I would always have a quick look at
second baby - first baby
perhaps plotted against their mean. If babies are better logged or
otherwise transformed, that's a further wrinkle.
Nick
[email protected]
Kit Baum
Ali said
I have a small data set of 136 infants each 2 of them have the same
mother. All mothers have a disease which I am at its effect on
birthweight. These women were diagnosed and treated after giving birth
for the first child. I am trying to measure the difference in mean
birthweight between infants who were born before treatment and those
who were born after treatment. At the same time I want to account for
parity (3 categories 1, 2 or 3) and gestational age (4 categories).
I am using regress with robust option to account for the fact that the
data is not independent. Is there a way to include the mothers
personal number in the model? Or does robust take into this problem
into account?
The model I used is x: regress birthweight i.disease i.parity
i.gestationalage, robust
why not cluster(motherid) ? That subsumes robust and allows for error
correlation among children of the same mother.
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