Re: st: Re: single sample pre/post comparison of proportions

["Michael I. Lichter" <mlichter@buffalo.edu>]

Thanks for the clarification, José. -ml

José Maria Pacheco de Souza wrote:
> <for the server>
>
> Perhaps  using the percentage of good habit already known as a lower
> bound p(known), test a hypothesis Ha: p(new)>p(known) vs H0:
> p(new)=p(known), using the at risk of improving.
>    p(known) is the best (highest) you have just before your new 
> hypothesis testing.
> Regards,
> José Maria
>
>
> Jose Maria Pacheco de Souza, Professor Titular (aposentado)
> Departamento de Epidemiologia/Faculdade de Saude Publica, USP
> Av. Dr. Arnaldo, 715
> 01246-904  -  S. Paulo/SP - Brasil
> fones (11)3061-7747; (11)3768-8612;(11)3714-2403
> www.fsp.usp.br/~jmpsouza
> ----- Original Message ----- From: "Michael I. Lichter" 
> <mlichter@buffalo.edu>
> To: <statalist@hsphsun2.harvard.edu>
> Sent: Thursday, June 11, 2009 2:10 PM
> Subject: Re: st: Re: single sample pre/post comparison of proportions
>
>
> > Svend: The researcher who asked me about this likes the idea of 
> > reporting CIs and forgoing the explicit hypothesis test.
> >
> > José: Unfortunately, it looks like the server ate the first line of 
> > your post so I'm not certain what you're suggesting. Is p(known) the 
> > pre-intervention proportion of adopters, is it an external estimate, 
> > or is it something else? If it's the first, I'm not sure I could 
> > justify that as a benchmark.
> >
> > Thanks to both of you for your suggestions.
> >
> > Michael
> >
> > José Maria Pacheco de Souza wrote:
> > > bound p(known), test a hypothesis Ha: p(new)>p(known) vs H0: 
> > > p(new)=p(known), using the at risk of improving.
> > >    Or as Svend presented, just estimate the proportion of new, among 
> > > those at risk. In this case, aftward it will difficult to resist the 
> > > temptation to compare this result with the p(known).
> > > Cheers,
> > > José Maria
>
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--
Michael I. Lichter, Ph.D. <mlichter@buffalo.edu>
Research Assistant Professor & NRSA Fellow
UB Department of Family Medicine / Primary Care Research Institute
UB Clinical Center, 462 Grider Street, Buffalo, NY 14215
Office: CC 126 / Phone: 716-898-4751 / FAX: 716-898-3536

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