# RE: st: negative and positive maximum likelihood ratios

 From "Donald Spady" <[email protected]> To <[email protected]> Subject RE: st: negative and positive maximum likelihood ratios Date Wed, 31 Jan 2007 08:17:20 -0700

```Nicola
Thanks for the response.  Further exploration of my problem led to the
realization that I wanted likelihood ratios and I was able to get what I
needed from -diagt-.  It also provided the LR's for a positive response and
a negative one.  So, I guess I sent you on a wild goose chase.  Sorry for
that.

-----Original Message-----
From: [email protected]
[mailto:[email protected]] On Behalf Of
[email protected]
Sent: January 31, 2007 1:07 AM
To: [email protected]
Cc: [email protected]
Subject: Re: st: negative and positive maximum likelihood ratios

Sorry for the delay in my replay and for potential double posting.
I am not sure if I understand correctly your questions.
-lrtest- provides a value (that reported besides "LR chi2") which is minus
the double of the difference of the Log likelihood (that value usually
reported before the table of the estimates; if you don't find it, you can
have it by typing -estat ic- and looking at the column "ll(model)") between
the two models you want to test. Simple example: if L0 is the log likelihood
for the constant-only model and L1 the log likelihood for the full model,
LR chi-squared = - 2 x (L0 - L1).
Given that it is a chi-squared, this value should be positive (I don't
understand what "1" matters: as I have shown above, despite being called
"ratio", it is not). But I have readen something among Stata's help files
(sorry, do not remember which one, probably an user-written command)
suggesting that a negative chi-squared points to strongly accepting the null
hypothesis.
Nicola

At 02.33 29/01/2007 -0500, Don Spady wrote:
>Can someone please tell me what the difference is between a negative
>and a positive maximum likelihood ratio.  My intuition tells me that a
>'negative' MLR is one that is less than 1 and a 'positive' MLR is
>greater than 1 but I cannot find anything that describes these terms.
>   As a second request: how does one calculate these ratios when doing
>logistic regression.  I know that you can test the ratios using lrtest
>but how can one actually calculate the ratio.

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```

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