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Re: st: Multilevel models with plausible values as dependent variable


From   Nailing Xia <[email protected]>
To   [email protected]
Subject   Re: st: Multilevel models with plausible values as dependent variable
Date   Fri, 29 May 2009 14:49:47 -0400

Thanks, I will try.

Regarding to the quesion on random effects/fixed effects, I am
estimating two levels: student, and school. After checking the data,
we decide to model the intercept as random effect rather than fixed
effects. I thought that, as long as the model has random effect terms,
I can only estimate a random effect model and a fixed effect model
won't work. Is this understanding incorrect?

On Fri, May 29, 2009 at 12:17 PM, Austin Nichols
<[email protected]> wrote:
> Nailing Xia <[email protected]> :
> Instead of using -pv-, first -reshape- the data so that each plausible
> value is a separate observation (on a person? are these math test
> scores?) and specify that as another level (multiple observations on a
> unit at a point in time) in -gllamm- etc. You may also want to weight
> by the variance of plausible outcomes, taking account of the greater
> uncertainty in some units' plausible values--see e.g.
>  http://www.stata.com/statalist/archive/2005-10/msg00079.html
> though this would be more of an issue if you were to take the mean of
> the plausible values as your outcome variable rather than using each
> as a separate observation (AFAIK you can only have one weight for each
> observation in Stata, not separate precision and sampling weights as
> in HLM, so I would multiply them all together and treat as pweights if
> you take this approach).
>
> You may want to check you get the same answer using my -reshape-
> approach in the unweighted case...  I have never used the user-written
> -pv- but some experimentation may be required to get matching results.
> -pv- seems to take various different approaches to combining
> estimates, and I have not looked up its references--maybe you can
> provide us some more context on your data.
>
> You did not answer: if the only random effect is the intercept, why
> not use fixed effects?  If you are not trying to estimate variability
> in heterogeneous coefficients, go with the method that requires fewer
> assumptions.  Or do you not have multiple points in time for each
> unit?
>
> You can't treat your sampling weights as frequency weights to -expand-
> for other reasons (inappropriate variance estimates).
>
> On Fri, May 29, 2009 at 11:41 AM, Nailing Xia <[email protected]> wrote:
>> Thanks for the reply. Here are more details on my problem.
>>
>> I am estimating multilevel models with random effect intercepts. The
>> dependent variable is measured using plausible values, therefore I
>> tried to use the user-written package -pv- for estimation as follows:
>> pv escs age female grade immg hmlang public city rural clsize scmatedu
>> [pw=w_fstuwt], pv(pv*math) cmd("xtmixed") cmdops("|| schid:") brr
>> rw(w_fstr*) fays(0.5)
>>
>> The error message is "weights not allowed", so I guess -xtmixed- does
>> not work with -pv-. I have tried -gllamm- with -pv- as well, and it
>> gives the same error message.
>>
>> I believe that making the dataset unweighted or using frequency
>> weights will not solve my problem either. My main issue is that the
>> dependent variable uses plausible values, and hence I have to use -pv-
>> for estimation. -pv- requires weights, so I need either find a command
>> for multilevel random effects models that allows weights, or find an
>> alternative to -pv- that handles plausible values.
>>
>> Any thoughts would be very much appreciated!
>>
>> Nailing Xia
>>
>> On Fri, May 29, 2009 at 10:47 AM, Austin Nichols
>> <[email protected]> wrote:
>>> Nailing Xia <[email protected]> :
>>> -gllamm- can handle this case; -findit gllamm- and read a few hundred
>>> pages of references...
>>> Do you need a multilevel model or can you specify fixed effects
>>> (faster and easier, and often more theoretically defensible)?
>>>
>>> On Fri, May 29, 2009 at 9:50 AM, Nailing Xia <[email protected]> wrote:
>>>> I am estimating a multilevel model using command -xtmixed-. The
>>>> dependent variable is measured with plausible values and Stata has the
>>>> command -pv- that handles such situation. However, -pv- does not seem
>>>> to work with -xtmixed-, it gives me error message "weights not
>>>> allowed". Does anyone know why I am getting this error message, or
>>>> other Stata command that handles plausible values with multilevel
>>>> models? I appreciate your help!
>>>>
>>>> Nailing Xia
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