Dear Apollo team!
I would like to ask you about a specific case of the hybrid choice model.
What should I do in case my latent variable is a categorical dichotomous variable?
I understand that the choice model part can be easily solved through an interaction, e.g:
b_price_new=b_price + lambda*LV ...
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Search found 18 matches
- 09 Apr 2025, 10:57
- Forum: Model specification
- Topic: Handling the dichotomous latent variable
- Replies: 3
- Views: 190984
- 08 Jul 2021, 09:39
- Forum: Post-estimation analysis/use of results
- Topic: Effect of latent variable in interaction
- Replies: 10
- Views: 37894
Re: Effect of latent variable in interaction
Thank you so much for your help Stephane!
- 07 Jul 2021, 18:27
- Forum: Post-estimation analysis/use of results
- Topic: Effect of latent variable in interaction
- Replies: 10
- Views: 37894
Re: Effect of latent variable in interaction
Hi Stephane,
thank you very much for your help!
I just tried to use the WTP-space transformation (it worked perfectly for the other models) in order to reach a consistent approach for all models analyzed (to avoid future criticism from reviewer).
Based on your suggestion, in this case I should ...
thank you very much for your help!
I just tried to use the WTP-space transformation (it worked perfectly for the other models) in order to reach a consistent approach for all models analyzed (to avoid future criticism from reviewer).
Based on your suggestion, in this case I should ...
- 05 Jul 2021, 14:34
- Forum: Post-estimation analysis/use of results
- Topic: Effect of latent variable in interaction
- Replies: 10
- Views: 37894
Re: Effect of latent variable in interaction
Hi Stephane,
I copy the code used to estimate the ICLV model.
rm(list = ls())
library(apollo)
apollo_initialise()
apollo_control = list(
modelName ="MLM_based_ICLV",
modelDescr ="MLM_based_ICLV",
indivID ="ID",
mixing = TRUE,
nCores = 4
)
database = read.csv("database.csv",header=TRUE ...
I copy the code used to estimate the ICLV model.
rm(list = ls())
library(apollo)
apollo_initialise()
apollo_control = list(
modelName ="MLM_based_ICLV",
modelDescr ="MLM_based_ICLV",
indivID ="ID",
mixing = TRUE,
nCores = 4
)
database = read.csv("database.csv",header=TRUE ...
- 05 Jul 2021, 07:25
- Forum: Post-estimation analysis/use of results
- Topic: Effect of latent variable in interaction
- Replies: 10
- Views: 37894
Re: Effect of latent variable in interaction
Hi Stephane!
Thank you for the quick and useful answer!
For solution one:
So, for example if I use WTP-space transformation (V_indication=b_indication+b_indication_shift_lambda*LV -> U=b_cost*(V_indication*Indication_alti +....), is it enough to interpret "b_indication" and ignore the "b ...
Thank you for the quick and useful answer!
For solution one:
So, for example if I use WTP-space transformation (V_indication=b_indication+b_indication_shift_lambda*LV -> U=b_cost*(V_indication*Indication_alti +....), is it enough to interpret "b_indication" and ignore the "b ...
- 04 Jul 2021, 16:14
- Forum: Post-estimation analysis/use of results
- Topic: Effect of latent variable in interaction
- Replies: 10
- Views: 37894
Effect of latent variable in interaction
Hi David and Stephane!
Unfortunately, I have a problem with interpreting my ICLV model results.
I would like to estimate the following structure: (1) MNL model, (2) MNL model with latent variable, (3) Mixed logit model, (4) Mixed logit model with latent variable.
I have one latent variable, and ...
Unfortunately, I have a problem with interpreting my ICLV model results.
I would like to estimate the following structure: (1) MNL model, (2) MNL model with latent variable, (3) Mixed logit model, (4) Mixed logit model with latent variable.
I have one latent variable, and ...
- 03 Feb 2021, 18:51
- Forum: Model estimation
- Topic: WTP-space estimates in latent class context
- Replies: 14
- Views: 44752
Re: WTP-space estimates in latent class context
Hi Stephane!
Thank you for your answers!
It became completely understandable to me.
I'm just trying to test and compare results in some model specifications.
To this point, I have found that (on other databases) in case of MNL and LC models, the two approaches were completely the same ...
Thank you for your answers!
It became completely understandable to me.
I'm just trying to test and compare results in some model specifications.
To this point, I have found that (on other databases) in case of MNL and LC models, the two approaches were completely the same ...
- 31 Jan 2021, 20:51
- Forum: Model estimation
- Topic: WTP-space estimates in latent class context
- Replies: 14
- Views: 44752
Re: WTP-space estimates in latent class context
Thank you Stephane!
The log-likelihood function reached earlier the point of convergation but the received (WTP) parameters were near identical than I get with 0 starting values.
I don't understand how I get so different results by using deltha method and WTP-space.
with 0.01 starting values for ...
The log-likelihood function reached earlier the point of convergation but the received (WTP) parameters were near identical than I get with 0 starting values.
I don't understand how I get so different results by using deltha method and WTP-space.
with 0.01 starting values for ...
- 28 Jan 2021, 19:35
- Forum: Model estimation
- Topic: WTP-space estimates in latent class context
- Replies: 14
- Views: 44752
Re: WTP-space estimates in latent class context
Hi Stephane,
I used 0 starting value for every parameters, both in preference- and WTP-space estimation.
Peter
I used 0 starting value for every parameters, both in preference- and WTP-space estimation.
Peter
- 28 Jan 2021, 13:39
- Forum: Model estimation
- Topic: WTP-space estimates in latent class context
- Replies: 14
- Views: 44752
Re: WTP-space estimates in latent class context
- Results of two-class LC model (in preference space)
Model diagnosis : successful convergence
Number of individuals : 261
Number of observations : 2088
Number of cores used : 3
Model without mixing
LL(start) : -2293.902
LL(0) : -2293.902
LL(final, whole model) : -2043.342
LL(component_1 ...
Model diagnosis : successful convergence
Number of individuals : 261
Number of observations : 2088
Number of cores used : 3
Model without mixing
LL(start) : -2293.902
LL(0) : -2293.902
LL(final, whole model) : -2043.342
LL(component_1 ...