Dear all,
someone asked that I post the code I used. It is a long program so I'm pasting
in the relevant parts:
. /*Total private*/
. generate privatecost=0
. replace privatecost=parkingcost+taxicost+carcost if tmode==1
(23856 real changes made, 4 to missing)
. save Logitmodes, replace
file Logitmodes.dta saved
. /*Total cost of using public transit:*/
. generate publiccost=0
. replace publiccost=(vp40_6+vp40_8+vp40_9+vp40_10)/100 if tmode==2
(11888 real changes made)
. save Logitmodes, replace
file Logitmodes.dta saved
************
. generate pphhpriv=pphh*private
. generate en1priv=en1*private
. generate en2priv=en2*private
. generate incpppriv=incpp*private
. generate vehicspriv=privehics*private
. generate locpriv=location*private
. generate hhincpriv=survhhinc*private
. generate sexpriv=sex*private
. generate headpriv=hofh*private
. generate emppriv=empl*private
**********************************
. clogit choice private incpppriv vehicspriv pphhpriv locpriv blckpriv sexpriv
headpriv emppriv pub
> lictime privatetime, group (numob)
note: 7614 groups (7614 obs) dropped due to all positive or
all negative outcomes.
Iteration 0: log likelihood = -23280.907
Iteration 1: log likelihood = -17006.85
Iteration 2: log likelihood = -16748.949
Iteration 3: log likelihood = -16745.97
Iteration 4: log likelihood = -16745.968
Iteration 5: log likelihood = -16745.968
Conditional (fixed-effects) logistic regression Number of obs = 68660
LR chi2(11) = 14099.55
Prob > chi2 = 0.0000
Log likelihood = -16745.968 Pseudo R2 = 0.2963
------------------------------------------------------------------------------
choice | Coef. Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
private | -.3507557 .0679412 -5.16 0.000 -.483918 -.2175933
incpppriv | .0048378 .0005038 9.60 0.000 .0038504 .0058252
vehicspriv | 1.362893 .0289785 47.03 0.000 1.306096 1.41969
pphhpriv | -.2289017 .0083926 -27.27 0.000 -.2453508 -.2124525
locpriv | -.147314 .029848 -4.94 0.000 -.205815 -.088813
blckpriv | -.0042336 .0005498 -7.70 0.000 -.0053111 -.0031561
sexpriv | -.1134412 .0298782 -3.80 0.000 -.1720013 -.0548811
headpriv | 1.589408 .0398303 39.90 0.000 1.511342 1.667474
emppriv | .8384917 .0303313 27.64 0.000 .7790434 .8979399
publictime | .0041342 .0006889 6.00 0.000 .002784 .0054844
privatetime | -.0099765 .0007839 -12.73 0.000 -.0115128 -.0084401
------------------------------------------------------------------------------
. clogit, or
Conditional (fixed-effects) logistic regression Number of obs = 68660
LR chi2(11) = 14099.55
Prob > chi2 = 0.0000
Log likelihood = -16745.968 Pseudo R2 = 0.2963
------------------------------------------------------------------------------
choice | Odds Ratio Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
private | .7041558 .0478412 -5.16 0.000 .6163637 .8044525
incpppriv | 1.00485 .0005062 9.60 0.000 1.003858 1.005842
vehicspriv | 3.90748 .113233 47.03 0.000 3.691732 4.135836
pphhpriv | .7954067 .0066755 -27.27 0.000 .78243 .8085987
locpriv | .8630229 .0257595 -4.94 0.000 .8139836 .9150167
blckpriv | .9957754 .0005474 -7.70 0.000 .994703 .9968489
sexpriv | .8927567 .0266739 -3.80 0.000 .8419781 .9465977
headpriv | 4.900848 .1952023 39.90 0.000 4.532811 5.298768
emppriv | 2.312876 .0701525 27.64 0.000 2.179387 2.454541
publictime | 1.004143 .0006917 6.00 0.000 1.002788 1.005499
privatetime | .9900731 .0007761 -12.73 0.000 .9885532 .9915954
------------------------------------------------------------------------------
*********************
Dear all,
I have two questions about clogit: one, about whether or not I "fed" the data
correctly to Stata, the second, about the sign on my coefficients. I do
appologize if there is a simple answer that I overlooked.
1. I've "fed" data that is alternative specific to find the choice=1 of using
private transportation versus choice=0 of using public transit. I have
sociodemographic variables and generic variables too, but my concern is with
the alternative specific variable of mode cost. The format I used was the
following for all ID's, can anybody tell me if this is wrong and if so, how to
fix it (I couldn't find more information in the Stata manual that might help).
Id Mode Choice Car-Cost Public-transit-Cost
32 1 1 120 0
32 2 0 0 20
Did I do the right thing by putting in the cost of using a car when the mode is
a car and zero in car cost when the mode is public?
2. I obtain a POSITIVE coefficient from public transit cost. My
interpretation
is that the more public tranist costs, the less we are likely to want to use it
and we may substitute to a car. I interpret this assuming that the model is
estimating V1-V2 (utility of driving - utility of using public transit) as in
the logit equations. This would imply that the coefficient for public transit
cost is negative in the utility of using public transit, but changes sign to
positive when we subtract that utility from utility of driving. I wanted to
check with you if this interpretation is correct, or do I, in fact, have the
wrong sign?
Any help you can give me would be immensely appreciated.
Sincerely,
Julia A. Gamas
Mexico City Project, EAPS
77 Massachusetts Avenue 54-1823
Cambridge, MA 02139
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