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From |
Laurel Copeland <[email protected]> |

To |
"'[email protected]'" <[email protected]> |

Subject |
st: RE: RE: RE: More on clogit: two questions |

Date |
Wed, 19 Jan 2005 10:45:30 -0600 |

You are right - she already has such an indicator. I'd forgotten. -----Original Message----- From: Leonelo Bautista [mailto:[email protected]] Sent: Wednesday, January 19, 2005 10:30 AM To: [email protected] Subject: st: RE: RE: More on clogit: two questions I don't think using an indicator for public vs. private would work. As you can see in the example, all choice=1 would have Public=0 and all choice=0 will have Public=1. Thus, there would be no variability in outcome for levels of "Public" and the model should not converge if public is included as a predictor. BTW, I still wondering what's your matching variable. Leonelo Bautista -----Original Message----- From: [email protected] [mailto:[email protected]] On Behalf Of Laurel Copeland Sent: Wednesday, January 19, 2005 8:20 AM To: '[email protected]' Cc: 'Julia Gamas' Subject: st: RE: More on clogit: two questions You could use an indicator for Public v Private, so your vars would be Id Mode Choice Cost Public 32 1 1 120 0 32 2 0 20 1 -----Original Message----- From: Julia Gamas [mailto:[email protected]] Sent: Wednesday, January 19, 2005 7:43 AM To: [email protected] Subject: st: More on clogit: two questions Hi again, the reason I've separated cost into public and private is because I'm assuming that they are perceived differently by the user (Ben-Akiva&Lerman 1985 have an example of such a model in their text book). So my question would then be, how CAN I include alternative specific variables into the conditional logit model in Stata? Thanks for any help. Julia > Date: Tue, 18 Jan 2005 10:24:57 -0500 > From: Julia Gamas <[email protected]> > Subject: st: clogit: two questions > > 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 > > Date: Tue, 18 Jan 2005 10:01:21 -0600 > From: Leonelo Bautista <[email protected]> > Subject: st: RE: clogit: two questions > > Julia, > - -clogit- is used for matched data. I guess your ID variable identifies the matching pair and that you are using this variable in the -group- option > - -group(id))-. I think you should have only one variable for transportation cost. So, for the first subject of the pair cost==120 and for the second > subject cost==20. In the way you have your data now, the outcome variable > (mode) is completely identifiable by the independent variables (all choice=1 have public cost=0 and all choice=0 have private cost=0). I don't think you can get meaningful results in this way. > > Leonelo Bautista > Date: Tue, 18 Jan 2005 11:38:34 -0500 > From: Julia Gamas <[email protected]> > Subject: st: clogit two question addendum-code > > 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 ---------------------------------------------------------------------------- * * For searches and help try: * http://www.stata.com/support/faqs/res/findit.html * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

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