Dear Chihmao,
You're right, the manual is so out-of-date
that it doesn't mention factor scoring!
It is very easy to obtain factor scores
(empirical Bayes predictions, equivalent to
the regression method for continuous responses)
using the prediction command gllapred:
gllapred scores, fac
The manual also doesn't say much about
adaptive quadrature which I would expect
to work much better than ordinary
quadrature for count-data. Simply
add the 'adapt' option to the gllamm
command.
Best wishes,
Sophia
At 12:01 AM 9/12/2003 -0500, you wrote:
>Dear Sophia:
>
>
>Thank you for your response. I have read chapter 4 as you suggested,
>but I am a little unclear as to the capability of this GLLAMM program to
>create scoring coefficients after running the factor analysis.
>
>
>Chihmao.
>
>-----------------------------------------------------
>Chihmao Hsieh
>John M. Olin School of Business
>Washington University
>Box 1133, One Brookings Drive
>St. Louis, MO 63130
>Email: [email protected]
>http://students.olin.wustl.edu/~hsieh
>
>
>-----Original Message-----
>From: [email protected]
>[mailto:[email protected]] On Behalf Of Sophia
>Rabe-Hesketh
>Sent: Monday, September 08, 2003 1:47 PM
>To: [email protected]
>Subject: st: Re: Factor analysis of count data
>
>
>Dear Chihmao Hsieh,
>
>You can estimate confirmatory factor models for count-data
>(and many other response types) by maximum likelihood
>using gllamm. gllamm uses adaptive quadrature to evaluate
>the likelihood. If your model involves only one or two factors, it
>shouldn't take that long to estimate the model.
>
>For more information on gllamm, see
>
>http://www.iop.kcl.ac.uk/IoP/Departments/BioComp/programs/gllamm.html
>
>You may find Chapter 4 of the gllamm manual useful.
>
>Best regards,
>
>Sophia
>
>----- Original Message -----
>From: "Chih-Mao Hsieh" <[email protected]>
>To: <[email protected]>
>Sent: Monday, September 08, 2003 6:13 PM
>Subject: st: Factor analysis of count data
>
>
>> Dear Statalisters,
>>
>>
>> While work has been done on developing factor analytical methods for
>non-normal data like categorical variables, less has been done until
>recently on factor analysis of count data. Is there any technical
>information on how STATA might handle factor analysis of count data
>(especially code)? I've looked at the manuals but have not found good
>stuff. I expect my observations numbering in the tens of thousands, and
>significant levels of overdispersion.
>>
>> Many thanks for any advice.
>>
>>
>> Chihmao Hsieh
>> PhD candidate, Strategy
>> Olin School of Business
>> Washington University in St. Louis
>>
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