Speaking of Stata, here's what I get for your original question (i.e., sample
size
for proportions of .085 & .045):
. power twoproportions .085 .045
Performing iteration ...
Estimated sample sizes for a two-sample proportions test
Pearson's chi-squared test
Ho: p2 = p1 versus Ha: p2 != p1
Study parameters:
alpha = 0.0500
power = 0.8000
delta = -0.0400 (difference)
p1 = 0.0850
p2 = 0.0450
Estimated sample sizes:
N = 1192
N per group = 596
I found this site helpful in working out how to do that:
http://www.stata-press.com/manuals/power-sample-size-reference-manual/HTH.
Dale Glaser wrote
> Greetings all....I have a
> question/situation that on the surface seems very transparent but I am
> having
> difficulties navigating. So any feedback will be much appreciated.
>
>
> For a study two years
> ago I conducted a power analysis comparing two proportions (p1 = .085 vs.
> p2 =
> .045). Whether I used
G*Power, Stata, or Power and Precision they all
> gave me
> sample size estimates ranging from 600 to 640 (contingent if continuity
> correction was incorporated) per group for alpha = .05 and power of .80.
>
>
>
> However, when I ran the
> SPSS macro for z test of proportions for two groups comparing .045 vs.
> .085, I found that n = 300 per
> group was sufficient to obtain significance: z = -1.99, p = .047. I also
> confirmed this in Stata using the following syntax: prtesti 300 .045 300
> .085.
>
> Hence, can I assume that
> the difference (i.e., n = 600 per group per power analysis vs. n = 300 per
> group being sufficient to obtain significance) is a function of the
> desired
> power insofar with the conventional power of .80 you are setting the bar
> high
> enough so as to find the optimal nexus of Type I and Type II error?
>
> The conundrum is such
> that our study ended up with p1 = .027 vs. p2 =.047 and p = .194 with the
> recommended sample
> size being n = 300 per
group given the simulation I ran in SPSS and
> Stata. Note that post hoc power analysis indicates I
> would have needed n = 1496 per group (alpha =.05, power = .80) to obtain
> significance
> for delta of 2%, though when I run .027 vs. .047 in Stata and SPSS with n
> = 685
> per group z = 1.96, p = .05.
>
> Anyway, this has become
> an interesting/challenging discussion with PI and reviewers alike. We
> went with the sample size (n = 300 per
> group) since that was sufficient for obtaining significance, but they are
> indicting we
> should have gone with the larger sample size based on the power estimate
> (i.e.,
> n = 600 per group).
>
> Has anyone encountered
> such a dilemma and how did you deal with it?
>
> Thank you….Dale
>
>
>
>
>
>
> Dale Glaser, Ph.D.
> Principal--Glaser Consulting
> Lecturer/Adjunct Faculty--SDSU/USD/Alliant
> 3115 4th Avenue
> San Diego, CA 92103
> phone: 619-220-0602
> fax: 619-220-0412
> email:
> glaserconsult@
> website: www.glaserconsult.com
>
>
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-----
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