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From |
Nick Cox <njcoxstata@gmail.com> |

To |
"statalist@hsphsun2.harvard.edu" <statalist@hsphsun2.harvard.edu> |

Subject |
Re: st: How to maximize an approximated likelihood |

Date |
Mon, 8 Apr 2013 10:18:47 +0100 |

You asked the same question a few days ago at http://www.stata.com/statalist/archive/2013-04/msg00152.html and no-one answered. The Statalist FAQ has advice on what to do if no-one answers. One repost, as here, is allowed, but it's best to think why no-one answered and try to rephrase the question. In this case, your problem seems a long way away from standard -ml- problems, as no response variable is evident, so I suspect that too many user-programmers found your question unclear and/or too complicated to try to understand. I hope you get a better answer, but the same question is not going to be any easier to understand. Nick njcoxstata@gmail.com On 8 April 2013 09:04, Feddag Mohand-Larbi <Mohand-Larbi.Feddag@univ-nantes.fr> wrote: > Dear Statausers, > > I am wondering to know how to maximize an approximated likelihood > depending on three parameters: the difficulty parameter as matrix, the > mean of the latent traits and its variance. > > The function wrotten in Stata where the approximation is obtained by > Gauss-Hermite quadrature is given as follows: > > qui gen proba=. > qui gen x=. > forvalues i=1/`nbobs' { > local int2=1 > local u=RaschDepLoc[`i',1] > local v=`diff'[1,1] > local int1 "exp(`u'*(x-`v'))/(1+exp(x-`v'))" > forvalues j=2/`nbitems' { > local t=`diff'[`j',1] > local r=RaschDepLoc[`i',`=`j-1''] > local s=RaschDepLoc[`i',`j'] > local int2 > "`int2'*exp(`s'*(x-`t'+`d'*`r'))/(1+exp(x-`t'+`d'*`r'))" > } > local int="`int1'*`int2'" > qui gausshermite `int', mu(`mu') sigma(`sigma') display > qui replace proba=r(int) in `i' > > } > gen lik=log(proba)*`nbobs' > > where nbobs is the number of individuals, nbitems is the number of > items, RaschDepLoc is the matrix of data of order (nbobs*nbitems), diff > is the vector of difficulties parameters, mu and sigma^2 are the mean > and the variance of the latent traits. > > I don't know how to write this function in order to use ml model lf myfunction (? =?) > and ml maximize > > > best > > > Dr Feddag > > > > > > > > > > > > > > * > * For searches and help try: > * http://www.stata.com/help.cgi?search > * http://www.stata.com/support/faqs/resources/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/faqs/resources/statalist-faq/ * http://www.ats.ucla.edu/stat/stata/

**References**:**st: How to maximize an approximated likelihood***From:*Feddag Mohand-Larbi <Mohand-Larbi.Feddag@univ-nantes.fr>

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