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RE: st: Logit transformation


From   jverkuilen <jverkuilen@gc.cuny.edu>
To   <statalist@hsphsun2.harvard.edu>
Subject   RE: st: Logit transformation
Date   Fri, 8 Aug 2008 12:14:55 -0400

I just want to second the recommendation of Long & Freese book Marten mentioned. 

You will also benefit from Googling for UCLA's ATS pages on Stata (I am on a handheld, can't do it). Also there are course notes by German Rodriguez at Princeton and some by Rich Williams from Notre Dame you may find helpful. 



-----Original Message-----
From: hounaz@uni-hohenheim.de
To: statalist@hsphsun2.harvard.edu
Sent: 8/8/2008 6:30 AM
Subject: Re: st: Logit transformation

Hello,

Thank you for your explanation. This is what I am trying to do. I want  
to relate the probability of being poor to the logit coefficients in a  
linear function.


Zitat von "Maarten buis" <maartenbuis@yahoo.co.uk>:

> --- hounaz@uni-hohenheim.de wrote:
>> I would to ask you a technical question on the transformation of
>> logit coefficients into non-negative weights.
>>
>> For example, I have run a logit regression which gave the following
>> results:
>>
>> logodds= 0.2198*agrhh +0.7161*ea_trad_boma - 0.0673*ruralnorth
>>            + 0.1807*ruralcentre - 0.4402*ruralsouth;
>>
>> odds= p/(1-p) is the odd ratio
>> p is the probability of being poor the explanatory variables are all
>> categorical and take the value of 0 or 1.
>>
>> Now, I want to transform all of the coefficients into non-negative
>> integers (based on a linear relationship as above) so that the
>> prediction of the logodds  ranges from 0 to 100.
>
> What I think you want to know is how the explanatory variables
> influence the probability of being poor. The fact that the probability
> is a number between 0 and 1 (or 0 and 100, if you prefer to think in
> terms of percentages) does not mean that the effects have to be
> positive. I certainly does not mean that the effect has to be an
> integer, this is not true for the probability either. An excelent text
> on interpreting these kinds of models is J. Scott Long & Jeremy
> Freese's "Regression Models for Categorical Dependent Variables Using
> Stata" published by the Stata Press:
> http://www.stata-press.com/books/regmodcdvs.html .
>
> Anyhow, if my assumption of what you want is correct, the command you
> are looking for is -mfx-, see -help mfx-.
>
> Hope this helps,
> Maarten
>
> -----------------------------------------
> Maarten L. Buis
> Department of Social Research Methodology
> Vrije Universiteit Amsterdam
> Boelelaan 1081
> 1081 HV Amsterdam
> The Netherlands
>
> visiting address:
> Buitenveldertselaan 3 (Metropolitan), room Z434
>
> +31 20 5986715
>
> http://home.fsw.vu.nl/m.buis/
> -----------------------------------------
>
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