Dear Maarten,
Thank you for your reply. I have compared models and used the likelihood ratio test subsequently.
I guess that the value of any single likelihood as it stands is not terribly important but is more useful when compared to another model.
Thank you.
Sincerely,
Gauri
> Date: Sun, 7 Oct 2007 18:43:46 +0100
> From: [email protected]
> Subject: Re: st: from Gauri (posting troubles) re positive log-likelihood
> To: [email protected]
>
> --- Gauri wrote:
>> I get the following value for the Log likeihood = 97
>>
>> How can I interpret this?
>>
>> I understand that a positive log likelihood is not unknown when the
>> dependant variable is continuous which is true for my case.
>>
>> However, I am stuck with the interpretation and can't express it in
>> words.
>
> In case of a continuous depedent variable the log likelihood is not the
> log of a probability (which must remain below zero) but a probability
> density (from the probability density function). The probability
> density is not bounded to be less than or equal to one, so the log
> likelihood is not bounded to be negative. The value of one log
> likelihood is not so interpretable on its own, the real power is in
> comparing (nested) models (e.g. through a likelihood ratio test or
> BICs/AICs).
>
> Hope this helps,
> Maarten
>
> -----------------------------------------
> Maarten L. Buis
> Department of Social Research Methodology
> Vrije Universiteit Amsterdam
> Boelelaan 1081
> 1081 HV Amsterdam
> The Netherlands
>
> visiting address:
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>
> +31 20 5986715
>
> http://home.fsw.vu.nl/m.buis/
> -----------------------------------------
>
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