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st: RE: Meta regression


From   "Long Nguyen" <long@drnguyen.org>
To   <statalist@hsphsun2.harvard.edu>
Subject   st: RE: Meta regression
Date   Tue, 15 May 2007 09:07:40 -0400

Hi, 

I would like to know how to use Stata to combine the effect size such as
control respond rate or active treatment respond rate in a meta analysis and
to generate Confidence Interval for them as well.

Thank you for your kind assistance.

Long


-----Original Message-----
From: owner-statalist@hsphsun2.harvard.edu
[mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Long Nguyen
Sent: Monday, May 14, 2007 4:13 PM
To: statalist@hsphsun2.harvard.edu
Subject: st: Meta regression

Hi, 

I'm a new user of STATA and trying to perform a meta regression.  I would
appreciate some detail instruction and examples or tutorials that can help
me do meta regression using this new tool.  I have the Getting Started..
Manual and installed the metareg module; however, the online help file
offered only limited information.

Thank you for your kind assistance,

Long

-----Original Message-----
From: owner-statalist@hsphsun2.harvard.edu
[mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Brian P. Poi
Sent: Monday, May 14, 2007 11:03 AM
To: statalist@hsphsun2.harvard.edu
Subject: Re: st: Different numbers of observations in sureg

On Mon, 14 May 2007 09:16:36 -0400 Alemu Mekonnen wrote:

> I would like to use different number of observations in the different 
> equations when using the seemingly unrelated regression command in stata 
> (i.e., sureg). For example, if there are two equations, I wanted to use 
> 600 observations for equation 1 and 900 observations for equation 2. My 
> question is how do I limit the number of observations to do this. I was 
> not able to use the IF command but this applies to all the equations in 
> the system.

Alemu,

Allen McDowell illustrates a clever way of fitting the SUR model with 
unequal numbers of observations by using the -xtgee- command in a "From 
the help desk" article in the Stata Journal (vol. 4, no. 4).

The trick is to recognize that the SUR model

    y1 = x1 * b1 + u1
    y2 = x2 * b2 + u2

can be "stacked" and written as

    [ y1 ] = [ x1  0 ][ b1 ] + [ u1 ]
    [ y2 ]   [  0 x2 ][ b2 ] + [ u2 ]

The stacked version looks just like a panel data model with two panels. 
One thing to note is in a SUR model, u1 and u2 are allowed to have 
different variances, while -xtgee- assumes they have a common variance. 
McDowell's article shows how to rescale the data using OLS regression and 
how to manipulate your dataset to use with -xtgee-.  Then to fit the model 
you simply use -xgee- with a Gaussian distribution, identity link 
function, and an unstructured correlation matrix.

    -- Brian Poi
    -- bpoi@stata.com


Reference
------------
McDowell, A.W. (2004). From the help desk: Seemingly unrelated regression
    with unbalanced equations.  Stata Journal, 4(4): 442-448.


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