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From |
Richard Williams <[email protected]> |

To |
[email protected] |

Subject |
Re: st: you estimated at least as many quantities as you have observations |

Date |
Fri, 05 Oct 2007 08:56:36 -0400 |

At 08:20 AM 10/5/2007, Maarten buis wrote:

It is possible too that missing data and/or subsample selection criteria are resulting in a small sample. If you think you should have a lot more cases than you actually do, check the descriptive stats for the vars involved in the analysis and see if there is something that is zapping your sample size.You estimated a model with exactly the same number of parameters as the number of observations. People who don't know statistics often fuss about how many observations they have, that is not really the problem (though often a reasonable approximation). The real problem is how many observations you have compared to the number of parameters you are estimating. If you are estimating a lot of parameters you need a lot of observations. In your case you either have a very large model or a very small data set, either way I would not put great value on your results.

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Richard Williams, Notre Dame Dept of Sociology

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**References**:**st: you estimated at least as many quantities as you have observations***From:*"Koksal, Bulent" <[email protected]>

**Re: st: you estimated at least as many quantities as you have observations***From:*Maarten buis <[email protected]>

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