From wgreene at stern.nyu.edu Tue Dec 1 05:41:16 2020
From: wgreene at stern.nyu.edu (William Greene)
Date: Mon, 30 Nov 2020 13:41:16 -0500
Subject: [Limdep Nlogit List] Nlogit simulation method
In-Reply-To:
References:
Message-ID:
Thao: The answer to your question depends on how you specified the
simulation. NLOGIT
carries out the simulation you specify it. In general, the ;SIMULATE
option for the NLOGIT
or CLOGIT routine works as follows.
(1) The base case is not the ASC only model. (You could specify it to be -
I'll look at that below.)
The base case is the data as they are in the sample. Probabilities are
computed for each
observation in the current sample using the model that has just been
estimated and the data
in the current sample.
(2) The simulation scenario consists of a set of one or more changes in
attributes. Step
(1) is repeated, but for each observation, the change in the attribute is
applied before the
probabilities are computed. The change in the attribute may be a change,
such as a 1% change
in travel time, or it might be to fix an attribute to a particular value
for everyone.
The four part setup you list below is actually how NLOGIT does the
calculations, save for the
specification of the base case. You can specify the fixed base case the
way you want as
follows: Note first that the simulator is worked on the data, any subset of
the data, or a
completely different set of observations. So, to fix the base, you would
create a single
artificial observation that contains the precise base case you want. You
can then run the
simulation using that single observations with a simulated scenario. This
is rather like
computing partial effects, however, which can be done much easier using the
specific tools
for that purpose. The simulator tries to predict the number of
observations in base and
changed cases, which would not be useful if you were just computing the
probabilities for
a single base case and a single change to that base.
Regards,
Bill Greene
On Mon, Nov 30, 2020 at 5:25 AM Thao Thai via Limdep <
limdep at mailman.sydney.edu.au> wrote:
> Hi Nlogit users,
>
> I would be grateful if you could explain how Nlogit undertakes the
> simulation method which is descried in nlogit manual:
> (1) base case is ASC only model (which means all attributes take on Zero)
> (2) Change one or some attribute value
> (3) Here is what I am confused about: *How did Nlogit arrives the
> probabilities of choosing for each alternative *
> - Assume other attributes takes zero except changed attribute take the
> values specified in (2)
> OR
> - Other attributes take values as is in the data and the changed
> attribute take the new value specified in (2)
>
> This is because I am not sure if the simulation described in Nlogit is
> similar to the "predictive uptake analysis" usually done in Health
> Economics literature and they call it "simulation". The process is:
> (1) specify a base case in which all attributes take on fixed
> values and calculate probabilities of choosing each alternative
> (2) change values of one or some attributes
> (3) recalculate the probabilities of choosing each alternative
> (4) the differences between probabilities of choosing the same
> alternative before and after are attributable to the change of
> attribute values.
>
>
> My second question: *How does Nlogit undertake the simulation using a mixed
> logit model?* Does it simply use the mean value of coefficients or does
> nlogit incorporate the distribution of coefficients in their calculation?
>
> Thank you so much. I look forward to seeing your explanation.
> Thao
> --
> *Thao Thai*| MHEcon(Adv), BPharm
> PhD candidate
> Centre for Health Economics
> Monash Business School | Monash University
> Tel (03) 99029847| Thao.T.Thai at monash.edu
> _______________________________________________
> Limdep site list
> Limdep at mailman.sydney.edu.au
> https://protect-au.mimecast.com/s/J_3SC71R2NT0qX11sWDOIV?domain=limdep.itls.usyd.edu.au
>
>
--
William Greene
Department of Economics, emeritus
Stern School of Business, New York University
44 West 4 St.
New York, NY, 10012
URL: https://protect-au.mimecast.com/s/HGRKC81V0PTAr5ppS2eyw_?domain=people.stern.nyu.edu
Email: wgreene at stern.nyu.edu
Editor in Chief: Journal of Productivity Analysis
Editor in Chief: Foundations and Trends in Econometrics
Associate Editor: Economics Letters
Associate Editor: Journal of Business and Economic Statistics
From Thao.T.Thai at monash.edu Fri Dec 4 16:38:10 2020
From: Thao.T.Thai at monash.edu (Thao Thai)
Date: Fri, 4 Dec 2020 16:38:10 +1100
Subject: [Limdep Nlogit List] MXL model: changing reference alternative-
inconsistent ASCs
Message-ID:
Dear Professor Greene and Nlogit users,
Thank you so much for answering my questions so far. I deeply appreciate
your help!
I have another issue that I would be grateful if you could help me with.
I have a stated preference data with 6 alternatives: HOS, COM, PRI, IND,
GOV, NON. When I changed the reference alternative (from HOS to COM), while
the ASCs results from CL models are consistent, the results from the mixed
logit models are not consistent in terms of signs. Please see the results
below, the ASC of HOS (compared to COM) and the ASC of COM (compared to
HOS) are both negative. I would expect the signs of ASCs should be opposite
given the two ASCs of HOS and COM are statistically significant in mixed
logit. The log likelihood values of two MXL models are different too.
I even tried ASCs only models and models with ASCs specified as dummy or
effect coded variables. The ASC results of the mixed logit models are not
consistent when I changed the reference alternative.
I would be truly grateful if you could suggest what has gone wrong.
My coding for the mixed logit models is below. I have the seed number for
them.
*HOS as the reference alternative*
*CL *model: logL = -4001.83388
COM| -.10806 .15871 -.68 .4959 -.41913 .20300
PRI| .40590*** .14002 2.90 .0037 .13146 .68034
IND| -1.11685*** .15286 -7.31 .0000 -1.41645 -.81725
GOV| -.07470 .14043 -.53 .5948 -.34993 .20053
NON| -.26651* .14521 -1.84 .0665 -.55112 .01810
*Mixed logit *model: logL = -3949.60375
|Random parameters in utility
functions..............................
COM| -.62569*** .23365 -2.68 .0074 -1.08362 -.16775
PRI| .23861 .17884 1.33 .1821 -.11191 .58914
IND| -1.75203*** .22127 -7.92 .0000 -2.18572 -1.31835
GOV| -.22635 .19028 -1.19 .2342 -.59930 .14660
NON| -.86462*** .23917 -3.62 .0003 -1.33338 -.39585
*COM as the reference alternative*:
*CL* model: logL = -4001.83388
HOS| .10806 .15871 .68 .4959 -.20300 .41913
PRI| .51396*** .15789 3.26 .0011 .20451 .82342
IND| -1.00878*** .18703 -5.39 .0000 -1.37535 -.64222
GOV| .03337 .16450 .20 .8392 -.28904 .35577
NON| -.15844 .17278 -.92 .3591 -.49709 .18020
*Mixel logit* model: logL = -3945.57277
|Random parameters in utility
functions..............................
HOS| -.46844** .22207 -2.11 .0349 -.90369 -.03319
PRI| .29024 .19299 1.50 .1326 -.08801 .66849
IND| -1.60623*** .25165 -6.38 .0000 -2.09946 -1.11301
GOV| -.19455 .20915 -.93 .3523 -.60448 .21538
NON| -.75668*** .25507 -2.97 .0030 -1.25662 -.25675
*Coding *
CALC ; Ran(12345) $
sample;all$
reject;sprp=1$
Nlogit
;lhs = cho, cset, alti
;choices = H, C, P, I, G, N
;checkdata
;Export output
;export=both
;rpl
;fcn= com(n), pri(n), ind(n), gov(n), non(n)
;pts=200
;pds=set
;halton
;maxit=300
;model:
U(H) = rlh1 * RL_H1 + rlh2 * RL_H2
+ fl * FL_H
+ crh1 * CR_H1 + cr2 * CR_H2
+ loh1 * LO_H1
+ sa * SA_H
/
U(C) = com + rlc1 * RL_C1 + rlc2 * RL_C2
+ fl * FL_C
+ crc1 * CR_C1 + cr2 * CR_C2
+ loc1 * LO_C1 + loc2 * LO_C2
+ sa * SA_C
/
U(P) = pri
+ rlp1 * RL_P1
+ fl * FL_P
+ crp1 * CR_P1 + cr2 * CR_P2
+ lop1 * LO_P1 + lop2 * LO_P2
+ sa * SA_P
/
U(I) = ind
+ rli1 * RL_I1 + rli2 * RL_I2
+ fl * FL_I
+ cri1 * CR_I1
+ loi1 * LO_I1
+ sa * SA_I
/
U(G) = gov
+ rlg1 * RL_G1
+ fl * FL_G
+ crg1 * CR_G1
+ log1 * LO_G1
+ sa * SA_G
/
U(N) = non
+ rln1 * RL_N1
+ fl * FL_N
+ crn1 * CR_N1
+ lon1 * LO_N1 + lon2 * LO_N2
+ sa * SA_N
$
Thank you so much!
Best regards,
Thao
From aahm7538 at uni.sydney.edu.au Tue Dec 8 18:47:09 2020
From: aahm7538 at uni.sydney.edu.au (Akram Ahmad)
Date: Tue, 8 Dec 2020 07:47:09 +0000
Subject: [Limdep Nlogit List] Nlogit Error 352: Model with Panel. Sum of
T(i) not equal to full sample size
Message-ID:
Hi everybody,
I have a question regarding Mixed logit model. For my research I want to investigate patients' preferences for conventional or Ayurvedic medicines for the treatment of diabetes and investigate what factors could affect patients' preferences.
In a labelled d-efficient design, which will have 3 alternatives where the last alternative would be a no-choice alternative. There were 8 attributes (7 of them have 3 levels and 1 attribute has 2 levels). We will be giving 8 choice tasks to each participant and block the design into 4 versions (for 32 tasks). Negative signs in the values indicate that the particular attribute will negatively contribute to the utilisation of the given alternative. For example, side-effects will decrease the utility of the medication (both conventional and alternative).
Here is my syntax for your perusal. The syntax error is popping up [Error 352: Model with Panel. Sum of T(i) not equal to full sample size]
Any help would be appreciated.
Mixed logit model
NLOGIT
;lhs=choice,cset,altij
;choices=CM,AM,NEITHER
;rpl
;fcn=effec(n),sidef(n),dosage(n),formu(n),instruct(n),hypo(n),weight(n),cost(n)
;pts=500 ;halton
;pds=nchoice
;model:
U(cm)=cm+effec1*effec1+ effec2*effec2+ sidef1*sidef1+sidef2*sidef2+dosage1*dosage1+ dosage2*dosage2+formu1*formu1+formu2*formu2+instruct*instruct+hypo1*hypo1+hypo2*hypo2+weight1*weight1+weight2*weight2+cost1*cost1+cost2*cost2/
U(am)=am+effec1*effec1+ effec2*effec2+ sidef1*sidef1+sidef2*sidef2+dosage1*dosage1+ dosage2*dosage2+formu1*formu1+formu2*formu2+instruct*instruct+hypo1*hypo1+hypo2*hypo2+weight1*weight1+weight2*weight2+cost1*cost1+cost2*cost2/
U(neither)=0
$
Regards,
Akram Ahmad
PhD student at School of Pharmacy, the University of Sydney.
From medakseth at gmail.com Tue Dec 8 19:16:38 2020
From: medakseth at gmail.com (medard kakuru)
Date: Tue, 8 Dec 2020 11:16:38 +0300
Subject: [Limdep Nlogit List] Nlogit Error 352: Model with Panel. Sum of
T(i) not equal to full sample size
In-Reply-To:
References:
Message-ID:
Dear Ahmed, it's about 6 years since a last used Nlogit but I noticed some
issues in your syntax.
(1) try removing cset and altij from lhs specification
(2) while specify fcn, you never disintegrated the attributes to their
levels just like you did in the utility specification.
Lastly, I am worried you may not get significant results because 8 choice
sets are too many to evaluate.
Otherwise, well done.
Regards,
Medard
On Tue, 8 Dec 2020, 10:47 Akram Ahmad via Limdep, <
limdep at mailman.sydney.edu.au> wrote:
> Hi everybody,
>
> I have a question regarding Mixed logit model. For my research I want to
> investigate patients' preferences for conventional or Ayurvedic medicines
> for the treatment of diabetes and investigate what factors could affect
> patients' preferences.
>
> In a labelled d-efficient design, which will have 3 alternatives where the
> last alternative would be a no-choice alternative. There were 8 attributes
> (7 of them have 3 levels and 1 attribute has 2 levels). We will be giving 8
> choice tasks to each participant and block the design into 4 versions (for
> 32 tasks). Negative signs in the values indicate that the particular
> attribute will negatively contribute to the utilisation of the given
> alternative. For example, side-effects will decrease the utility of the
> medication (both conventional and alternative).
> Here is my syntax for your perusal. The syntax error is popping up [Error
> 352: Model with Panel. Sum of T(i) not equal to full sample size]
> Any help would be appreciated.
>
> Mixed logit model
>
> NLOGIT
> ;lhs=choice,cset,altij
> ;choices=CM,AM,NEITHER
> ;rpl
>
> ;fcn=effec(n),sidef(n),dosage(n),formu(n),instruct(n),hypo(n),weight(n),cost(n)
> ;pts=500 ;halton
> ;pds=nchoice
> ;model:
> U(cm)=cm+effec1*effec1+ effec2*effec2+
> sidef1*sidef1+sidef2*sidef2+dosage1*dosage1+
> dosage2*dosage2+formu1*formu1+formu2*formu2+instruct*instruct+hypo1*hypo1+hypo2*hypo2+weight1*weight1+weight2*weight2+cost1*cost1+cost2*cost2/
> U(am)=am+effec1*effec1+ effec2*effec2+
> sidef1*sidef1+sidef2*sidef2+dosage1*dosage1+
> dosage2*dosage2+formu1*formu1+formu2*formu2+instruct*instruct+hypo1*hypo1+hypo2*hypo2+weight1*weight1+weight2*weight2+cost1*cost1+cost2*cost2/
> U(neither)=0
> $
>
> Regards,
> Akram Ahmad
> PhD student at School of Pharmacy, the University of Sydney.
> _______________________________________________
> Limdep site list
> Limdep at mailman.sydney.edu.au
> https://protect-au.mimecast.com/s/25OzCWLVXkUK9VvRI6oAkC?domain=limdep.itls.usyd.edu.au
>
>
From wgreene at stern.nyu.edu Wed Dec 9 01:46:06 2020
From: wgreene at stern.nyu.edu (William Greene)
Date: Tue, 8 Dec 2020 09:46:06 -0500
Subject: [Limdep Nlogit List] Nlogit Error 352: Model with Panel. Sum of
T(i) not equal to full sample size
In-Reply-To:
References:
Message-ID:
Akram Ahmad. When you use the NLOGIT estimator with stated choice data, it
is necessary
to indicate how many choice tasks there are, with the ;PDS specification,
as you have done.
The data set resembles a panel. However, using NLOGIT, rather than, say,
REGRESS, the
panel looks a bit different. Your observation consists of 8 tasks and 3
rows of data (alternatives)
per task. It seems like the panel should contain 24 rows per task. But,
your PDS correctly
specifies PDS = 8. NLOGIT resolves this as follows: There are two passes
through the data
to set up the model using panel, SP data. The first pass is generic,
before the program "knows" that
you will be fitting a choice model. If you specified PDS=8 at this point,
it looks like a mismatch
unless you happen to have number of observations equal to a multiple of 8,
which may or may
not be true. If not, the diagnostic occurs. At this point, the program
takes the next step and
assembles the structure of the data for the choice experiment, which has 8
tasks per chooser
and 3 alts per task. The match of the PDS to the data, with this revised
form, is checked. If you
have correctly provided 8 sets of 3 rows of data, this second check will
pass, and your results
will follow. The upshot is that you can ignore the error 352.
Regards
Bill Greene
On Tue, Dec 8, 2020 at 2:47 AM Akram Ahmad via Limdep <
limdep at mailman.sydney.edu.au> wrote:
> Hi everybody,
>
> I have a question regarding Mixed logit model. For my research I want to
> investigate patients' preferences for conventional or Ayurvedic medicines
> for the treatment of diabetes and investigate what factors could affect
> patients' preferences.
>
> In a labelled d-efficient design, which will have 3 alternatives where the
> last alternative would be a no-choice alternative. There were 8 attributes
> (7 of them have 3 levels and 1 attribute has 2 levels). We will be giving 8
> choice tasks to each participant and block the design into 4 versions (for
> 32 tasks). Negative signs in the values indicate that the particular
> attribute will negatively contribute to the utilisation of the given
> alternative. For example, side-effects will decrease the utility of the
> medication (both conventional and alternative).
> Here is my syntax for your perusal. The syntax error is popping up [Error
> 352: Model with Panel. Sum of T(i) not equal to full sample size]
> Any help would be appreciated.
>
> Mixed logit model
>
> NLOGIT
> ;lhs=choice,cset,altij
> ;choices=CM,AM,NEITHER
> ;rpl
>
> ;fcn=effec(n),sidef(n),dosage(n),formu(n),instruct(n),hypo(n),weight(n),cost(n)
> ;pts=500 ;halton
> ;pds=nchoice
> ;model:
> U(cm)=cm+effec1*effec1+ effec2*effec2+
> sidef1*sidef1+sidef2*sidef2+dosage1*dosage1+
> dosage2*dosage2+formu1*formu1+formu2*formu2+instruct*instruct+hypo1*hypo1+hypo2*hypo2+weight1*weight1+weight2*weight2+cost1*cost1+cost2*cost2/
> U(am)=am+effec1*effec1+ effec2*effec2+
> sidef1*sidef1+sidef2*sidef2+dosage1*dosage1+
> dosage2*dosage2+formu1*formu1+formu2*formu2+instruct*instruct+hypo1*hypo1+hypo2*hypo2+weight1*weight1+weight2*weight2+cost1*cost1+cost2*cost2/
> U(neither)=0
> $
>
> Regards,
> Akram Ahmad
> PhD student at School of Pharmacy, the University of Sydney.
> _______________________________________________
> Limdep site list
> Limdep at mailman.sydney.edu.au
> https://protect-au.mimecast.com/s/IrBbCD1vlpTzP1lwFWNFhF?domain=limdep.itls.usyd.edu.au
>
>
--
William Greene
Department of Economics, emeritus
Stern School of Business, New York University
44 West 4 St.
New York, NY, 10012
URL: https://protect-au.mimecast.com/s/7XKJCE8wmrt2Pm5OCwIVK3?domain=people.stern.nyu.edu
Email: wgreene at stern.nyu.edu
Editor in Chief: Journal of Productivity Analysis
Editor in Chief: Foundations and Trends in Econometrics
Associate Editor: Economics Letters
Associate Editor: Journal of Business and Economic Statistics
From drhumphrey.walker at yahoo.com Wed Dec 9 07:00:30 2020
From: drhumphrey.walker at yahoo.com (Humphrey Walker)
Date: Tue, 8 Dec 2020 20:00:30 +0000 (UTC)
Subject: [Limdep Nlogit List] Remove from mail list please
References: <1816887514.4931703.1607457630110.ref@mail.yahoo.com>
Message-ID: <1816887514.4931703.1607457630110@mail.yahoo.com>
Hi there,
Would you please remove me from your mail list :)
Best regards and merry Christmas
Humphrey Walker
From doctorjasonong at gmail.com Mon Dec 28 17:55:10 2020
From: doctorjasonong at gmail.com (Jason Ong)
Date: Mon, 28 Dec 2020 17:55:10 +1100
Subject: [Limdep Nlogit List] Can I use simulation command for RPL models?
Message-ID:
hi,
I am interested in running simulation models from an RPL model
but when I want to change the scenario, do I need to rerun the RPL each
time (takes an hour for each scenario)
or is there a way to run the RPL model (use a "$" before ;simulation) and
save it
then just run the simulation separately?
thanks for your help
NLOGIT
; Lhs = choicev, cset, altij
; Choices = A,B,C
; rpl
; fcn=cost1(n), cost2(n), cost3(n),loc1(n), loc2(n), loc3(n), loc4(n),
app1(n), app2(n), app3(n), result1(n), result2(n), result3(n), result4(n),
deliv1(n), deliv2(n), deliv3(n), deliv4(n), extra(n)
; pds=15
; pts=500
; halton
; Model:
U(A,B)=cost1*cost1+cost2*cost2+cost3*cost3+loc1*loc1+loc2*loc2+loc3*loc3+loc4*loc4+app1*app1+app2*app2+app3*app3
+result1*result1+result2*result2+result3*result3+result4*result4+deliv1*deliv1+deliv2*deliv2+deliv3*deliv3+deliv4*deliv4
+extra*extra/
U(C)=neither
;SIMULATION
;SCENARIO:cost1(a,b)={*}0/cost2(a,b)={*}1/cost3(a,b)={*}0/loc1(a,b)={*}-1/loc2(a,b)={*}-1/loc3(a,b)={*}-1/loc4(a,b)={*}-1/
app1(a,b)={*}1/app2(a,b)={*}0/app3(a,b)={*}0/result1(a,b)={*}0/result2(a,b)={*}1/result3(a,b)={*}0/result4(a,b)={*}0/
deliv1(a,b)={*}-1/deliv2(a,b)={*}-1/deliv3(a,b)={*}-1/deliv4(a,b)={*}-1/extra(a,b)={*}-1
&
cost1(a,b)={*}-1/cost2(a,b)={*}-1/cost3(a,b)={*}-1/loc1(a,b)={*}-1/loc2(a,b)={*}-1/loc3(a,b)={*}-1/loc4(a,b)={*}-1/
app1(a,b)={*}1/app2(a,b)={*}0/app3(a,b)={*}0/result1(a,b)={*}0/result2(a,b)={*}1/result3(a,b)={*}0/result4(a,b)={*}0/
deliv1(a,b)={*}-1/deliv2(a,b)={*}-1/deliv3(a,b)={*}-1/deliv4(a,b)={*}-1/extra(a,b)={*}-1
$
*Jason Ong*
From walibehram at yahoo.com Mon Dec 28 19:47:39 2020
From: walibehram at yahoo.com (Behram Wali)
Date: Mon, 28 Dec 2020 08:47:39 +0000 (UTC)
Subject: [Limdep Nlogit List] SALC models in NLOGIT?
In-Reply-To:
References:
Message-ID: <220624844.3035590.1609145259462@mail.yahoo.com>
Hi Jason:
Once a model has been estimated, you can run as many scenarios as desired. The model does not need to be re-estimated each time. To do so, first estimate the model so the results are stored and then re-run the same model command but with ;simulation option enabled to run a scenario. You can do repeat this for multiple scenarios. For your example, this would look like:
????? ************ Estimating the model firstNLOGIT; Lhs = choicev, cset, altij; Choices = A,B,C; rpl; fcn=cost1(n), cost2(n), cost3(n),loc1(n), loc2(n), loc3(n), loc4(n),app1(n), app2(n), app3(n), result1(n), result2(n), result3(n), result4(n),deliv1(n), deliv2(n), deliv3(n), deliv4(n), extra(n); pds=15; pts=500; halton; Model:U(A,B)=cost1*cost1+cost2*cost2+cost3*cost3+loc1*loc1+loc2*loc2+loc3*loc3+loc4*loc4+app1*app1+app2*app2+app3*app3+result1*result1+result2*result2+result3*result3+result4*result4+deliv1*deliv1+deliv2*deliv2+deliv3*deliv3+deliv4*deliv4+extra*extra/U(C)=neither$
????? *************** Simulating Scenario 1
NLOGIT; Lhs = choicev, cset, altij; Choices = A,B,C; rpl; fcn=cost1(n), cost2(n), cost3(n),loc1(n), loc2(n), loc3(n), loc4(n),app1(n), app2(n), app3(n), result1(n), result2(n), result3(n), result4(n),deliv1(n), deliv2(n), deliv3(n), deliv4(n), extra(n); pds=15; pts=500; halton; Model:U(A,B)=cost1*cost1+cost2*cost2+cost3*cost3+loc1*loc1+loc2*loc2+loc3*loc3+loc4*loc4+app1*app1+app2*app2+app3*app3+result1*result1+result2*result2+result3*result3+result4*result4+deliv1*deliv1+deliv2*deliv2+deliv3*deliv3+deliv4*deliv4+extra*extra/U(C)=neither;SIMULATION;SCENARIO:cost1(a,b)={*}0/cost2(a,b)={*}1/cost3(a,b)={*}0/loc1(a,b)={*}-1/loc2(a,b)={*}-1/loc3(a,b)={*}-1/loc4(a,b)={*}-1/app1(a,b)={*}1/app2(a,b)={*}0/app3(a,b)={*}0/result1(a,b)={*}0/result2(a,b)={*}1/result3(a,b)={*}0/result4(a,b)={*}0/deliv1(a,b)={*}-1/deliv2(a,b)={*}-1/deliv3(a,b)={*}-1/deliv4(a,b)={*}-1/extra(a,b)={*}-1&cost1(a,b)={*}-1/cost2(a,b)={*}-1/cost3(a,b)={*}-1/loc1(a,b)={*}-1/loc2(a,b)={*}-1/loc3(a,b)={*}-1/loc4(a,b)={*}-1/app1(a,b)={*}1/app2(a,b)={*}0/app3(a,b)={*}0/result1(a,b)={*}0/result2(a,b)={*}1/result3(a,b)={*}0/result4(a,b)={*}0/deliv1(a,b)={*}-1/deliv2(a,b)={*}-1/deliv3(a,b)={*}-1/deliv4(a,b)={*}-1/extra(a,b)={*}-1$
????? *************** Simulating Scenario 2NLOGIT; Lhs = choicev, cset, altij; Choices = A,B,C; rpl; fcn=cost1(n), cost2(n), cost3(n),loc1(n), loc2(n), loc3(n), loc4(n),app1(n), app2(n), app3(n), result1(n), result2(n), result3(n), result4(n),deliv1(n), deliv2(n), deliv3(n), deliv4(n), extra(n); pds=15; pts=500; halton; Model:U(A,B)=cost1*cost1+cost2*cost2+cost3*cost3+loc1*loc1+loc2*loc2+loc3*loc3+loc4*loc4+app1*app1+app2*app2+app3*app3+result1*result1+result2*result2+result3*result3+result4*result4+deliv1*deliv1+deliv2*deliv2+deliv3*deliv3+deliv4*deliv4+extra*extra/U(C)=neither;SIMULATION;SCENARIO:...$
Yours Sincerely,
Behram Wali, PhD | Lead Research Scientist
Urban Design 4 Health, Inc.| https://protect-au.mimecast.com/s/3i3YC71R2NTMpRQnT8UHeB?domain=ud4h.com | 24 Jackie Circle East, Rochester, NY 14612Office: (617) 207-9665 | C: (865) 306-6677 | Fax: (801) 335-1923 | Email: bwali at ud4h.comWebsite | Google ScholarSelf-expression and self-identification are part of my professional and personal values. One way to practice these values is to share personal gender pronouns. I use he, him, his pronouns.
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On Wednesday, August 26, 2020, 09:50:28 PM EDT, Jason Ong via Limdep wrote:
hi,
Is there the possibility to run scale-adjusted latent class models in
NLOGIT?
if not, will there be plans to do so?
thank for your help
Best,
*Jason Ong*
Twitter: @DrJasonJOng
PhD, MMed, MBBS, FAChSHM, FRACGP
Sexual Health Physician, Melbourne Sexual Health Centre, Alfred Health
Associate Professor (Hon), London School of Hygiene and Tropical Medicine,
UK
Central Clinical School, Monash University, Australia
Melbourne School of Population and Global Health, University of Melbourne,
Australia
Associate Editor, Sexually Transmitted Infections
Special Issues Editor, Sexual Health
Board Director, ASHM (https://protect-au.mimecast.com/s/qo9LC81V0PT3vkzBT1x89p?domain=ashm.org.au)
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