Statalist


[Date Prev][Date Next][Thread Prev][Thread Next][Date index][Thread index]

Re: st: Meta-analysis


From   "Tom Trikalinos" <ttrikalin@gmail.com>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: Meta-analysis
Date   Mon, 17 Mar 2008 14:52:59 -0400

yup, this is why this is a big topic ;-) ... with no easy answer...
conducting and interpreting sparse event meta-analysis is
challenging... especially when you find a difference in the end.

[and on top of that, as Ingram complains, no one uses the angular
(tukey-freeman) transformation ;) ]

t

On Mon, Mar 17, 2008 at 1:54 PM, Marcello Pagano
<pagano@hsph.harvard.edu> wrote:
> Welcome to one of the few areas in statistics where people promote
>  throwing data away with impunity.  One could say that whether you
>  discard experiments where there are no events on either arm, or not,
>  depends which side of the argument you are on.  Since no events on
>  either arm is evidence towards equality of the two arms, then throw the
>  data away if you are trying to show a difference :-)    Otherwise, why
>  throw the data away?
>
>  The usual reason proffered for discarding the data is that it is
>  embarrassing when looking at odds ratios to have to divide zero by zero.
>  But the question you have to ask yourself is why are you looking at odds
>  ratios?  If you have to, for example if you have a case-control study,
>  then you have a problem, otherwise stay clear of odds ratios and you
>  won't have a problem if you use appropriate methods for analysis.
>
>  m.p.
>
>
>
>  On 3/17/2008 1:24 PM, Tom Trikalinos wrote:
>  > this is a big topic.
>  > see for example:
>  >
>  > Stat Med. 2007 Jan 15;26(1):53-77. Much ado about nothing: a
>  > comparison of the performance of meta-analytical methods with rare
>  > events.   Bradburn MJ, Deeks JJ, Berlin JA, Russell Localio A.
>  >
>  > Stat Med. 2004 May 15;23(9):1351-75. What to add to nothing? Use and
>  > avoidance of continuity corrections in meta-analysis of sparse data.
>  > Sweeting MJ, Sutton AJ, Lambert PC.
>  >
>  > and quite a few other papers that are out there.  The ones discussing
>  > the recent rosiglitazone meta-analysis are also relevant. Do a PubMed
>  > search if you have not already.
>  >
>  > My take: Assuming you do not go Bayesian and that you use the typical
>  > garden variety meta-analysis methods:
>  >
>  > 1. Random effects per Der Simonian and Laird are probably a no for
>  > main analyses (biased tau^2 in simulation studies).
>  > 2. Peto OR seems to do well in terms of bias and coverage
>  > probabilities for the CI (!).
>  > 3. Mantel-Haenszel (MH) OR seems to do well, I presume the same for RR
>  > though i think this is not as clear, or so i remember.
>  > 4. M-H RD is reported to give somehow biased estimates and conservative CI
>  >
>  > 5. If you use multiplicative effect sizes - e.g. an OR I would
>  > calculate main analyses without 0% vs 0% studies, then add them in in
>  > a sensitivity analysis
>  >
>  > All the above allowing for the caveat that one an operational
>  > knowledge of the relevant methods literature and knowledge of which
>  > methods need fudge factors to correct for 0 cells...
>  >
>  > hope this helps
>  >
>  > tom
>  >
>  >
>  >
>  > On Mon, Mar 17, 2008 at 12:42 PM, Sripal Kumar <sripalkumar@gmail.com> wrote:
>  >
>  >> I was wondering what are your thoughts on meta analysis of trials with
>  >>  limited number of events.  Should studies with no events be censored
>  >>  from the analysis?
>  >>
>  >>  Any input is highly appreciated.
>  >>  thanks,
>  >>  Sripal.
>  >>
>  *
>  *   For searches and help try:
>  *   http://www.stata.com/support/faqs/res/findit.html
>  *   http://www.stata.com/support/statalist/faq
>  *   http://www.ats.ucla.edu/stat/stata/
>
*
*   For searches and help try:
*   http://www.stata.com/support/faqs/res/findit.html
*   http://www.stata.com/support/statalist/faq
*   http://www.ats.ucla.edu/stat/stata/



© Copyright 1996–2014 StataCorp LP   |   Terms of use   |   Privacy   |   Contact us   |   What's new   |   Site index