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Re: st: Gllapred and Level 2 Residuals


From   Jielu Lin <jielu.lin@case.edu>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: Gllapred and Level 2 Residuals
Date   Sat, 15 May 2010 11:02:34 -0400

That makes a lot of sense. Thank you!

Jielu

On Fri, May 14, 2010 at 11:01 PM, Stas Kolenikov <skolenik@gmail.com> wrote:
> You have numeric issues and/or identification problems in your model:
> the random intercepts and slopes are pretty much perfectly correlated
> (although negatively). That may be enough to break it down.
>
> With normal data, you might be better off with -xtmixed-. You will
> certainly get your estimates faster.
>
> On Fri, May 14, 2010 at 6:15 PM, Jielu Lin <jielu.lin@case.edu> wrote:
>> Dear all,
>>
>> I estimated a random coefficient model using gllamm and obtained level
>> 2 residuals using gllapred with ustd option. However, there were no
>> values for the residuals of the random slope (rz_iadl_q~m2 in the
>> output below) . Here is my output:
>>
>> . gllamm iadl age agesq , i(id) eqs(inter slope) nip(12) nrf(2) adapt
>> from(a) copy
>> number of level 1 units = 580
>> number of level 2 units = 145
>> Condition Number = 390550.68
>> log likelihood = -1081.5765
>> ------------------------------------------------------------------------------
>>      totiadl |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
>> -------------+----------------------------------------------------------------
>>         age |  -1.663252   .2012228    -8.27   0.000    -2.057641   -1.268862
>>       agesq |   .0118635    .001325     8.95   0.000     .0092667    .0144604
>>        _cons |   58.63494   7.653772     7.66   0.000     43.63382    73.63606
>> ------------------------------------------------------------------------------
>> Variance at level 1
>> ------------------------------------------------------------------------------
>>   1.3431285 (.10917208)
>> Variances and covariances of random effects
>> ------------------------------------------------------------------------------
>> ***level 2 (id)
>>     var(1): 125.06127 (29.45089)
>>     cov(2,1): -1.8267617 (.4144318) cor(2,1): -.99814552
>>     var(2): .02678263 (.00585232)
>> ------------------------------------------------------------------------------
>>
>> . gllapred rz_iadl_q_r, ustd
>> (means and standard deviations will be stored in rz_iadl_q_rm1
>> rz_iadl_q_rs1 rz_iadl_q_rm2 rz_iadl_q_rs2 )
>> Non-adaptive log-likelihood: -1081.3564 -1081.6149 -1081.5765
>> -1081.5765   log-likelihood:-1081.5765
>>
>> . su  rz_iadl_q_rm1 rz_iadl_q_rs1 rz_iadl_q_rm2 rz_iadl_q_rs2
>>     Variable |       Obs        Mean    Std. Dev.       Min        Max
>> -------------+--------------------------------------------------------
>> rz_iadl_q~m1 |       580   -.0277825    1.043866  -3.951646   2.430058
>> rz_iadl_q~s1 |       580    9.382843    .9076038   8.122407   10.82412
>> rz_iadl_q~m2 |         0
>> rz_iadl_q~s2 |         0
>>
>> Thanks everyone in advance!
>> Jielu Lin
>>
>> *
>> *   For searches and help try:
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>> *   http://www.ats.ucla.edu/stat/stata/
>>
>
>
>
> --
> Stas Kolenikov, also found at http://stas.kolenikov.name
> Small print: I use this email account for mailing lists only.
>
> *
> *   For searches and help try:
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> *   http://www.stata.com/support/statalist/faq
> *   http://www.ats.ucla.edu/stat/stata/
>

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