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st: Re: Regarding logit and probit model

From   Maarten Buis <[email protected]>
To   [email protected]
Subject   st: Re: Regarding logit and probit model
Date   Fri, 6 Jul 2012 13:03:42 +0200

Such questions need to be asked on Statalist and not to its individual
member, as is clearly stated on the Statalist FAQ:

Problem 1: I don't even think R-squared is useful in linear
regression, so I certainly don't thing the many "pseudo- R-squares"
that exist for models like -logit- or -probit- have any value.

Problem 2: I don't understand that question: you cannot estimate a
-probit- with -nlogit-. The -logit- and -probit- is so close (up to a
fixed factor) that the choice between them is purely arbitrary. The
most important factor influencing that choice is typically the tribal
habits of different (sub-(sub-))disciplines. It certainly has nothing
to do with one model being better at "eliminating unobserved error".

Problem 3: There is nothing you can meaningfully do about
heteroscedasticity in logit or probit models. Models exist, but they
are so sensitive that the results are basically meaningless.

-- Maarten

On Fri, Jul 6, 2012 at 11:19 AM, KADALI RAGHURAM wrote:
> Dear Maarten,
> Good morning,
> Greetings from B R KADALI,
> This is BR Kadali Research Scholar from IIT Bombay India,
> I working in Transportation Engineering, my area of Interest is "Pedestrian
> Flow Modeling under Mixed Traffic condition". Presently i am working with
> Pedestrian Gap acceptance behaviour, for this data analysis i am trying to
> uses discrete choice modeling LOGIT and PROBIT Models.
> Problem-1
> The problem here, i am struggling with MacFedden R-squared value. I got
> R-squared value around 0.784. But it is unfeasible values. I used LOGIT
> MODEL- There  are 4200 sample vehicular gaps i collected out these only 200
> gaps are accepted by pedestrian i.e., (Probability of accepted gaps=1=200
> sample) remain data samples are 4000 rejected values i.e., o coded values.
> So, my doubt here the R-squared value is acceptable or not. Now I converted
> data as maximum rejected gap and accepted gap now total data points 400 in
> this case also I got same R-sq 0.789. This R-sq value is acceptable or not.
> Problem-2
> When I build PROBIT model in the NLOGIT, I couldn’t get any much difference
> when compared with LOGIT model. The only difference I observed is
> coefficient values. But literature says that there is an improvement by
> probit model when compared to logit model by eliminating unobserved error
> like heteroscedasticity. It will be eliminated by PROBIT model, what are the
> difference can I observe here. In this case how can judge my model is better
> than the LOGIT model. If there is difference between LOGIT and PROBIT in the
> case of binary data, what is the reason behind it.
> Problem-3
> If I take model with LOGIT as HETROSCADACITY model, what improvement I can
> get, is it eliminating the unobserved error by gender and Age of the people.
> What are the main advantages over the simple LOGIT model and PROBIT model of
> HETROSCADACITY model?. If suppose in the HETROSCADACITY model the gender is
> getting significant, how can I represent the utility equations of this case.
> I am really sorry for the inconvenience, but I am really want some useful
> information about these doubts.
> I am waiting for valuable reply and suggestions
> Thank you
> --
> Regards
> B R Kadali

Maarten L. Buis
Institut fuer Soziologie
Universitaet Tuebingen
Wilhelmstrasse 36
72074 Tuebingen

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