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


From   "Michael I. Lichter" <mlichter@buffalo.edu>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: Re: single sample pre/post comparison of proportions
Date   Thu, 11 Jun 2009 16:10:11 -0400

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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