[Limdep Nlogit List] Fwd: SP to RP scale parameter in combined mixed logit

Zeinab Yahyazadeh Jasour zeinabj at udel.edu
Wed Jul 20 03:46:17 AEST 2016

Dear limdep user,

I have sent this question last week but I did not get any response back. I
really appreciate if anyone gives me any suggestion or recommends any
material that can help me find a solution for my problem? Moreover, I found
out that there is another model named GMXL to combine SP/RP, should I try

---------- Forwarded message ----------
From: Zeinab Yahyazadeh Jasour <zeinabj at udel.edu>
Date: Thu, Jul 14, 2016 at 11:58 AM
Subject: SP to RP scale parameter in combined mixed logit
To: limdep at limdep.itls.usyd.edu.au

Dear limdep users,

I'm having trouble running a combined RP/SP mixed logit model. I cannot
find the SP to RP scale parameter.  I tried checking the NLOGIT manuals and
"Applied Choice Analysis, 2nd edition”. On page 852 this book, the concept
of the SP scale parameter is discussed. It is stated there that you can
find the SP scale parameter based on standard deviation of ASC of
alternative, but this information is not in the output of our model.

The data I am analyzing comes from a discrete choice, choice experiment
survey. I have about 313 survey respondents that were each asked a yes or
no choice experiment question 3 times, one RP and two SP. My universal
choice set consists of 7 alternatives (one choice and a none alternative
for revealed preference, and four choices and a none for stated preference)
and each question consists of two alternatives (a choice and a none
alternative).  Thus, I have about 1878 rows of data. This is my current



    ;Choices=rpyes,rpno,spyes,spgyes,spryes,splyes, spno







U(rpyes)=R1           +WI*windinc+chi*CHILD+RA*RACE/


U(spyes)=NOI1       +WI*windinc+chi*CHILD+RA*RACE/

U(spgyes)=     G1       +WI*windinc+chi*CHILD+RA*RACE/

U(spRyes)=   PR1       +WI*windinc+chi*CHILD+RA*RACE/

U(splyes)=    LL1      +WI*windinc+chi*CHILD+RA*RACE/



And the output is as follow:

Random Parms/Error Comps. Logit Model

Dependent variable                STRAP

Log likelihood function     -7568.75368

Estimation based on N =    508, K =  14

Inf.Cr.AIC  =  15165.5 AIC/N =   29.853


            Log likelihood R-sqrd R2Adj

No coefficients  -988.5224 ************

Constants only can be computed directly

               Use NLOGIT ;...;RHS=ONE$

At start values -7887.7841  .0404 .0133

Note: R-sqrd = 1 - logL/Logl(constants)

Warning:  Model does not contain a full

set of ASCs. R-sqrd is problematic. Use

model setup with ;RHS=one to get LogL0.


Response data are given as ind. choices

Replications for simulated probs. = 150

Used Halton sequences in simulations.

RPL model with panel has     313 groups

Fixed number of obsrvs./group=        3

BHHH estimator used for asymp. variance

Number of obs.=   939, skipped  431 obs


        |                  Standard            Prob.      95% Confidence

   STRAP|  Coefficient       Error       z    |z|>Z*         Interval


        |Random parameters in utility

      WI|   -11.9917      .7322D+07      .00 1.0000 ***********  ***********

        |Nonrandom parameters in utility

      R1|    11.4509      .7322D+07      .00 1.0000 ***********  ***********

     CHI|     .15277         .40867      .37  .7085     -.64820    .95375

      RA|    -.49102         .55598     -.88  .3771    -1.58073    .59868

    NOI1|    8.68247      .7322D+07      .00 1.0000 ***********  ***********

      G1|     3251.0      .1218D+14      .00 1.0000 -.23868D+14  .23868D+14

     PR1|    27625.5      .9375D+13      .00 1.0000 ***********  ***********

     LL1|    166.500      .1128D+14      .00 1.0000 ***********  ***********

        |Distns. of RPs. Std.Devs or limits of

    NsWI|     .02295       23.31667      .00  .9992   -45.67688  45.72278

        |Standard deviations of latent random

SigmaE01|     .02779       20.41008      .00  .9989   -39.97523  40.03081

SigmaE02|     .03581       22.56064      .00  .9987   -44.18224  44.25387

SigmaE03|        0.0      .7832D+15      .00 1.0000 -.15351D+16  .15351D+16

SigmaE04|        0.0      .2999D+15      .00 1.0000 -.58777D+15  .58777D+15

SigmaE05|        0.0      .3843D+15      .00 1.0000 -.75323D+15  .75323D+15


nnnnn.D-xx or D+xx => multiply by 10 to -xx or +xx.

***, **, * ==>  Significance at 1%, 5%, 10% level.

Model was estimated on Jul 14, 2016 at 10:17:19 AM


I hope you can clarify this.

Thank you very much in advance!

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