--- [email protected] 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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