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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 > * > * For searches and help try: > * http://www.stata.com/help.cgi?search > * http://www.stata.com/support/statalist/faq > * http://www.ats.ucla.edu/stat/stata/ > * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

**References**:**st: Multilevel models with plausible values as dependent variable***From:*Nailing Xia <[email protected]>

**Re: st: Multilevel models with plausible values as dependent variable***From:*Austin Nichols <[email protected]>

**Re: st: Multilevel models with plausible values as dependent variable***From:*Nailing Xia <[email protected]>

**Re: st: Multilevel models with plausible values as dependent variable***From:*Austin Nichols <[email protected]>

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