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From |
Troy Hegel <troy.hegel@bio.uio.no> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: Cross-classified Random Coefficient Model with xtmelogit |

Date |
Wed, 16 Apr 2008 09:20:00 +0200 |

Thank you very much Bobby for your speedy response.

Your suggested work around does indeed work fine. And yes, the "5" in my original post was a typo and should have been a "7", my apologies for that.

Regards,

Troy

------------------------------

Date: Tue, 15 Apr 2008 14:42:19 -0500

From: rgutierrez@stata.com (Roberto G. Gutierrez, StataCorp)

Subject: Re: st: Cross-classified Random Coefficient Model with xtmelogit

Troy Hegel <troy.hegel@bio.uio.no> writes:

I am trying to fit a cross-classified mixed model in which Herd (n=10) and[...]

Year (n=27) are cross-classified random effects. The number of observations

for my model is 165.

Using the following syntax I can fit a cross-classified random intercept

model that yields sensible results:

xtmelogit Calves Treat Adj April || _all:R.Year || Herd: , binomial(Cows)

I am trying to fit "April" as a random coefficient on "Herd" and I thought

that this syntax should work, but I get the subsequent error message:

xtmelogit Calves Treat Adj April || _all:R.Year || Herd: April ,[...]

binomial(Cows)

initial vector: matrix must be dimension 5 r(503);[...]

Troy's syntax is indeed correct for the model he wishes to fit. Instead, he

has uncovered a bug in the initial-values logic for -xtmelogit-, a bug that

can be triggered in the specific case of cross-classified random effects

models with random coefficients in addition to random intercepts.

We'll fix this in the next ado update. In the meantime, Troy can work around

this bug by supplying his own initial values and by-passing the initial values

calculation altogether. A vector of zeros should suffice, if not, Troy can

email me privately and I can suggest some alternatives.

. mat b = J(1, 7, 0)

. xtmelogit Calves Treat Adj April || _all:R.Year || Herd: April ,

binomial(Cows) from(b)

The "7" in the above is for four fixed effects (three coefficients plus one

intercept) and three variance components; one at the Year level and two at the

Herd level (one random intercept and and one random coefficient on April).

Troy's error message indicates this number as "5", but it should be "7", and

in my tests to reproduce the bug it was. In any case, the discrepancy won't

matter once the bug is fixed.

- --Bobby

rgutierrez@stata.com

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