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st: RE: appropriate techniques for analysing suicide mortality data- xtreg fe? poisson?


From   "Lachenbruch, Peter" <[email protected]>
To   <[email protected]>
Subject   st: RE: appropriate techniques for analysing suicide mortality data- xtreg fe? poisson?
Date   Thu, 5 Mar 2009 09:24:56 -0800

There is a marvelous book by Andrew Gelman and Jennifer Hill on
techniques that will be helpful here.  It's published by Cambridge
University Press.  It's quite readable with many useful examples.

Tony

Peter A. Lachenbruch
Department of Public Health
Oregon State University
Corvallis, OR 97330
Phone: 541-737-3832
FAX: 541-737-4001


-----Original Message-----
From: [email protected]
[mailto:[email protected]] On Behalf Of
[email protected]
Sent: Wednesday, March 04, 2009 10:51 PM
To: [email protected]
Subject: st: appropriate techniques for analysing suicide mortality
data- xtreg fe? poisson?

Dear statalist, 
This is a question regarding the appropriateness of the techniques I
have chosen for my phd. Unfortunately, I do not have a statistician at
my uni who can provide me with an expert opinion on this- hence why I am
posting this message on stata list. I am sorry for the list of questions
that follow, but I would be truly grateful if any one can offer me
advise.

I have panel data containing suicide rates for 74 countries over a long
time series. I wish to test the relationship that these have with social
variables within the country (ie. Unemployment rate etc.,).
Suicide rates are transformed using the square root transformation and
social data is transformed using the ln transformation. 
Currently I have been using fixed/random effects to estimate the
relationship between these variables. I have also made a lagged model of
these relationships using xtabond2. 
However, I realise that researchers often use the poisson distribution
in conducting analysis with suicide data. Considering this, should I
stick to techniques that use this distribution (xtgee is one I know... I
am not sure about any others that may also use this)? or can I still use
the fixed/random effect models? Also, if I do need to use the poisson
distribution, how can I conduct my dynamic model? (I do realise that
Martin Weiss made some suggestions to me for this- thank you)

Thanks for your advice in advance.



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