I was going to ask the same thing. I don't see how SEs would be more
informative than CIs.
But -- if two (independent) estimates have the same precision (i.e.,
standard error), then one can show that their 83.4% CIs will just touch
when the (two-sided) p-value for a Wald-type test of the difference is
equal to .05. So, in that case, 83.4% CIs will directly tell you whether
the difference is significant or not.
Unfortunately, this doesn't work when the standard errors of the estimates
are not the same. The larger the difference in SEs, the wider one needs to
make the CI to have equivalence between 'non-overlap = significant
difference'.
Best,
Wolfgang
-----Original Message-----
From: R-sig-meta-analysis [mailto:
r-sig-meta-analysis-bounces at r-project.org]
On Behalf Of Gerta Ruecker
Sent: Thursday, 04 June, 2020 11:32
To: r-sig-meta-analysis at r-project.org
Subject: Re: [R-meta] Overlapping CIs with significant difference among
subgroups
Dear Rafael,
First of all, the information content of standard errors and confidence
intervals is identical, they can be transformed into each other.
Secondly, to present standard errors in a graph, one would probably show
x ? SE(x) instead of x ? 1.96*SE(x). But what would be the advantage?
The interpretation of this intercval would mean that the true value is
covered by 68% of all such intervals (=1-2*(1-pnorm(1))). I don't think
that this is of more interest than a confidence interval.
The main aim of a forest plot is interval estimation, not statistically
comparing different studies.
Best,
Gerta
Am 04.06.2020 um 08:26 schrieb Rafael Rios:
Dear Dr. Wolfgang,
Thank you for the feedback. I was wondering why meta-analysts did not
exhibit standard errors instead of confidence intervals in graphs. I can
understand the importance of showing that CIs did not include zero, but
standard errors can be more informative when comparing subgroups of a
moderator. This is just a curiosity.
Best wishes,
Rafael.