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From |
Nick Darson <nick.darson@googlemail.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: estimation of SE of correlation after mixlogit |

Date |
Fri, 12 Aug 2011 21:50:01 +1000 |

Dear Arne, Many thanks for your reply. I see now why my attempts using nlcom (with "v21" instead of the l21/l11 etc combos) did not work. And BTW: thank you very much for writing and sharing this great program! Cheers, Nick On Fri, Aug 12, 2011 at 9:26 PM, Arne Risa Hole <arnehole@gmail.com> wrote: > Nick > > Note that -mixlogit- is a user-written command which is available > from the SSC and described in > <http://www.stata-journal.com/article.html?article=st0133>. > > Running the following command after -mixlogit- (on one line) will give > you the SE of the correlation: > > nlcom (rho: [l21]_b[_cons]*[l11]_b[_cons] / > sqrt([l11]_b[_cons]*[l11]_b[_cons]*([l21]_b[_cons]*[l21]_b[_cons] + > [l22]_b[_cons]*[l22]_b[_cons]))) > > Arne > > On 12 August 2011 10:59, Nick Darson <nick.darson@googlemail.com> wrote: >> Hi listers, >> >> After running mixlogit, I am wondering how I exactly calculate the >> standard error of the correlation. >> >> To my understanding, I have to do this manually after obtaining the >> covariance-variance components using the command "mixlcov" (please >> tell me if there is an easier automatic way that I have overlooked, >> such as using nlcom - I have tried this but always get error >> messages). >> >> For example, I have a multinomial model with three possible >> alternatives: low, mid, high (low as the base case; mid and high are >> random and allowed to be correlated). >> >> Hence, after estimation with mixlogit and using "mixlcov", I obtain >> the values for v21, v11, and v22. >> >> This way I can easily calculate the correlation of the two variables: >> rho= _b[v21] / sqrt (_b[v11] * _b[v22]) >> >> However, how do I calculate the SE of this correlation? >> I found the following formula: SE(rho) = sqrt ( 1-rho^2 / n -2 ) >> >> However, which value do I use for "n"? In my case, I have repeated >> measures (each of the 200 individuals makes 5 choices). Hence, should >> I use n=200 (the number of subjects), n= 1000 (total number of >> observations), or do I need to look how many cases actually have >> chosen mid and high (e.g. let's say from the 1000 total choices, 200 >> are mid and 300 are high, hence n=500)? >> >> Thankful for any help on this apparently simple issue. >> >> Cheers, >> Nick >> * >> * 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/ > * * 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: estimation of SE of correlation after mixlogit***From:*Nick Darson <nick.darson@googlemail.com>

**Re: st: estimation of SE of correlation after mixlogit***From:*Arne Risa Hole <arnehole@gmail.com>

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