Unfortunately we don't document specific algorithms. You might be able
to find the information in the original packages we wrap.
Kosuke Imai
Princeton University
Sent from my iPhone
On Jun 24, 2009, at 6:01 PM, "Zhang, Hui"
<Hui_Zhang(a)URMC.Rochester.edu> wrote:
Dear Kosuke,
Now I am trying to compare different available package for fitting
longitudinal binary data using GLMM. I am just wondering which
algorithm you used in Zelig but I am not able to find this
information in zelig package and the website. Did you use either
linearization or approximating the loglikelihood?
Thank you very much!
Hui
-----Original Message-----
From: monkeykupo(a)gmail.com [mailto:monkeykupo@gmail.com] On Behalf
Of Olivia Lau
Sent: Monday, March 30, 2009 10:03 PM
To: Kosuke Imai
Cc: Zhang, Hui; Gary King; Tu, Xin; zelig(a)lists.gking.harvard.edu;
Delia Bailey
Subject: Re: [zelig] RE: a question regarding R package "Zelig"
Hi,
There's a trade-off between N (total number of units) and M (number of
clusters). These models are known to have some bias in situations
where the number of clusters M is small, or the number of units n_m in
each unit is large relative to the number of clusters. In order to
show that the results are unbiased, try running 100 simulations with
100 clusters, and 5 units in each cluster. The mean of the
simulations should return the true parameters to the first decimal
place. Additional precision can be achieved by increasing the number
of simulations.
Best,
Olivia
On Mon, Mar 30, 2009 at 10:27 PM, Kosuke Imai <kimai(a)princeton.edu>
wrote:
> Hi,
>
> I'm not familiar with these kinds of models, but I wouldn't be
> surprised if
> the convergence has not been achieved at n = 300. It's also
> possible that
> variance parameters have uncertainty estimation which has not been
> taken
> into account (although I'm not 100 % sure about if this is indeed
> the case,
> and I'm ccing to the contributor of this model to see if she has any
> insight). If this is the case, you might want to choose the bootstrap
> option.
>
> Kosuke
>
> --
> Department of Politics
> Princeton University
>
http://imai.princeton.edu
>
> On Mon, 30 Mar 2009, Zhang, Hui wrote:
>
>> Dear Kosuke,
>>
>> Thank you so much for your response. After I update all the three,
>> my R,
>> lme4 and Zelig packages, to the newest version, the problem
>> disappeared.
>>
>>
>> Then I tested the Zelig package for binary data GLMM modeling.
>> However,
>> I did not get the result as supposed.
>>
>> Basically, I generate the dataset from a GLMM model to and then
>> test the
>> type I error using Zelig fitting. It did not give the correct number
>> even for large sample size.
>>
>> I attached both the simulation strategy and R code in this email.
>> Do you
>> think that is because I did not use the the Package "Zelig"
>> correctly or
>> it has deficit?
>>
>> Thank you so much!
>>
>> Hui
>>
>> -----Original Message-----
>> From: Kosuke Imai [mailto:kimai@Princeton.EDU]
>> Sent: Sunday, March 29, 2009 9:34 PM
>> To: Zhang, Hui
>> Cc: Gary King; Delia Bailey; Tu, Xin; zelig(a)lists.gking.harvard.edu
>> Subject: Re: a question regarding R package "Zelig"
>>
>> Can you try the latest version of Zelig and lme4 and do:
>>
>> demo(ls.mixed)
>>
>> It works for me and should work for you too... Note that you
>> should do
>>
>> install.packages("Zelig", repos =
"http://gking.harvard.edu")
>>
>> for Zelig.
>>
>> Thanks,
>> Kosuke
>>
>>
>
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