Dear Nick, Sven and Nicholas,
Thank you very much! this is very helpful.
regards,
Gaby
--- Nick Cox <[email protected]> wrote:
> Svend had some very good advice here.
>
> Here's some more.
>
> 0. Whatever you do, it seems that you should look at
>
>
> females / (males + females)
>
> and also
>
> females / (males + females + unknown)
>
> 1. Plot your means against month.
>
> 2. If there's no seasonality there is little point
> to splitting by month.
>
> 3. If there is seasonality, the tacit assumption
> that
> separate months are mutually independent is
> unlikely. One
> way forward is a generalised linear model with
> binomial link and time of year as predictor.
> A trigonometric approach might help. See
>
> SJ-6-4 st0116 . . . . Speaking Stata: In praise
> of trigonometric predictors
> Q4/06 SJ 6(4):561--579
> (no commands)
> discusses the use of sine and cosine as
> predictors in
> modeling periodic time series and other
> kinds of periodic
> responses
>
> Nick
> [email protected]
>
> Svend Juul
>
> > Gaby Serdan wrote:
> >
> > I have data on deaths. I need to calculate the
> mean &
> > CI of females in proportion to all population. Im
> > trying first to create a variable for each month
> then
> > take the total number of female per month and then
> > divide by total number of deaths per month.
> >
> > - and Clive Nicholas gave suggestions.
> >
>
---------------------------------------------------------------
> >
> > I understand that you want to estimate the
> proportion
> > of females among the persons who died each month.
> The
> > data you provided are a bit surprising for the
> purpose,
> > with one female, three males, and 21 with unknown
> sex.
> > To create some more illustrative data, I:
> >
>
>
> *
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>
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