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From |
Austin Nichols <austinnichols@gmail.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: Cumulative probabilities |

Date |
Wed, 21 Oct 2009 08:02:10 -0400 |

Evans Jadotte <evans.jadotte@uab.es> : What's z in (z-xb-...) below? If you are calculating an estimate of e in the numerator, and dividing by the estimate of the SD of e, then you are calculating the Z score of the idiosyncratic error, and Phi(Z). What is this for? Can you provide refs for what "some books suggest" ? On Tue, Oct 20, 2009 at 11:16 AM, Evans Jadotte <evans.jadotte@uab.es> wrote: > Hello listers, > > Sorry for sending this message again but I realized some characters did not > appear too well. > > I am estimating cumulative probabilities of the following function: > > Yijk = b0 +b1Xijk + eijk + u.jk + u..k > > > > where u.jk and u..k are two random intercepts with variance Sigma^2 (u.jk) > and Sigma^2 (u..k). The variance of my raw residuals is Sigma^2 (eijk). The > cumulative probabilities I want to calculate are of the form: > > Phi((z-xb-uhat.jk - uhat../k/)/sqrt(?)) > > where Phi denotes the standard normal cumulative density. My question is: > should the square root, sqrt, in the denominator contain just the variance > of the raw residuals, i.e. Sigma^2 (eijk), as some books suggest? Or should > it bear, according to my logic, the total variance of the model, which would > be the sum Sigma^2 (e ijk) + Sigma^2 (u.jk) + Sigma^2 (u..k)? And finally, > what would be the statistics rationale for using the former instead of the > latter formula? > > Thanks in advance, > > Evans * * 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/

**Follow-Ups**:**Re: st: Cumulative probabilities***From:*Evans Jadotte <evans.jadotte@uab.es>

**References**:**st: Cumulative probabilities***From:*Evans Jadotte <evans.jadotte@uab.es>

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