Re: st: metareg of failure rates or proportions / meta-analysis of proportions

[salil deo <salildeo@gmail.com>]

Dear All,

While performing meta-analysis of proportions in Stata using the metan
command , recently found out that data can be entered using the syntax

metan p p_LL p_UL, fixed/random

is this a valid way run the test ... I have tried to read up
extensively on this topic from the  Statalist as well as the internet
.. The earlier posts in the Statalist used the "meta" command with the
" metagraph" command for the forest plot  but the "megan" command
presents much better graphs than the earlier metagraph one.

Mr Hoaglin has commented that inverse variance weighting creates bias
in this type of meta-analysis , then what method is preferable ?
Mantel-Haenzel method ?

Thanks,

Salil V Deo
On 6/21/13, Khairallah, Carole [khaicar]
<Carole.Khairallah@liverpool.ac.uk> wrote:
> Thank you very much for your reply, very clear.
> And now I am confident in not log-transforming my outcome.
>
> Carole Khairallah
>
>
> -----Original Message-----
> From: owner-statalist@hsphsun2.harvard.edu
> [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of David Hoaglin
> Sent: 21 June 2013 15:37
> To: statalist@hsphsun2.harvard.edu
> Subject: Re: st: metareg of failure rates or proportions
>
> Carole,
>
> As I understand it, -metareg- expects effect estimates whose behavior can
> reasonably be approximated by a normal distribution.  That's the main reason
> for using log of odds ratio and log of risk ratio.  It might be all right to
> use a proportion or a rate without transformation.  Proportions or rates
> based on rare events may need a transformation or a different analysis.
>
> In a meta-analysis of proportions the use of inverse-variance weights is a
> potential source of bias and should be avoided.
>
> I distinguish rates from proportions.  A proportion has a counted numerator
> and a counted denominator and may often be modeled by a binomial
> distribution.  Most rates have a different type of denominator.  Their
> estimated variances may not be so troublesome, depending on how they are
> calculated.
>
> You mentioned "betas from a previous regression model."  If those betas come
> from studies that have not used the same set of predictor variables in their
> regression models, they are generally not comparable.  For example, they may
> be the logs of adjusted odds ratios with adjustments for different sets of
> covariates.
>
> David Hoaglin
>
> On Fri, Jun 21, 2013 at 7:11 AM, Khairallah, Carole [khaicar]
> <Carole.Khairallah@liverpool.ac.uk> wrote:
>> Hi all,
>>
>> I would like to run a meta-regression on proportions using the metareg
>> command in Stata v12.1
>>
>> I've seen that odds ratio, hazard ratio, etc. have to be log-transformed
>> (log e or natural log) - which leads to use the betas from a previous
>> regression model as effect sizes in metareg.
>>
>> But if the outcome of interest is a proportion, particularly failure rates
>> computed from -strate ? A log-transformation (should write
>> ln-transformation) doesn't make sense there?
>>
>> Thanks for your help
>> Carole
> *
> *   For searches and help try:
> *   http://www.stata.com/help.cgi?search
> *   http://www.stata.com/support/faqs/resources/statalist-faq/
> *   http://www.ats.ucla.edu/stat/stata/
>
> *
> *   For searches and help try:
> *   http://www.stata.com/help.cgi?search
> *   http://www.stata.com/support/faqs/resources/statalist-faq/
> *   http://www.ats.ucla.edu/stat/stata/
>
*
*   For searches and help try:
*   http://www.stata.com/help.cgi?search
*   http://www.stata.com/support/faqs/resources/statalist-faq/
*   http://www.ats.ucla.edu/stat/stata/