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From |
"Michael Anthony Carlton" <carlto12@msu.edu> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: SUR and a system of logit models |

Date |
Sat, 26 Apr 2008 16:48:05 -0400 |

You are correct. Estimating these equations as a system will only gain efficiency. Because the logit is in the linear exponential family as long as the conditional mean function is modeled correctly you will have consistent parameter estimates.

F. Gao writes:

Dear all,

Thanks for your reply.

I actually have more than 2 equations that I am currently running

logistic regressions separately.

My understanding is that estimating them together would increase the

efficiency of the estimates. But is there anything strongly against

doing this instead of estimating a system of equations?

Any other suggestions?

Thanks!

Faye

If there is no STATA procedue, is there SAS procedure?

On 4/26/08, Phil Schumm <pschumm@uchicago.edu> wrote:

On Apr 25, 2008, at 4:53 PM, F. Gao wrote:*

> What to do if I have a system of logit models (binary dependent variables)

and wish to do SUR regression?

> eg: Pr(A=1)=f(x,y), Pr(B=1)=f(x,z)

>

On Apr 26, 2008, at 5:35 AM, Stephen P. Jenkins wrote:

> There is no such approach that I am aware of, as there is no multivariate

logistic distribution.

>

One possible approach is alternating logistic regression:

V. Carey, S. L. Zeger, and P. Diggle. Modelling multivariate binary data

with alternating logistic regressions. Biometrika, 80(3):517–526, 1993.

I am not aware of a Stata implementation.

-- Phil

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**References**:**RE:st: SUR and a system of logit models***From:*"Stephen P. Jenkins" <stephenj@essex.ac.uk>

**Re: st: SUR and a system of logit models***From:*Phil Schumm <pschumm@uchicago.edu>

**Re: st: SUR and a system of logit models***From:*"F. Gao" <gaofaye@gmail.com>

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