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Error when using mixed logit with only one observation per individual

Ask questions about errors you encouunter. Please make sure to include full details about your model specifications, and ideally your model file.
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victornielsen
Posts: 13
Joined: 19 Apr 2022, 15:49

Error when using mixed logit with only one observation per individual

Post by victornielsen »

Hello

I am trying to build a mixed ordered logit model with a random error term.

This is my model:

Code: Select all

#### nautos ####
# ################################################################# #
#### LOAD LIBRARY AND DEFINE CORE SETTINGS                       ####
# ################################################################# #

### Clear memory
rm(list = ls())
s12 <- read_csv("discretechoice.csv")


### Load Apollo library
library(apollo)

### Initialise code
apollo_initialise()

### Set core controls
apollo_control = list(
  modelName       = "MOLnautos",
  modelDescr      = "Mixed ordered logit model fitted to MOCOLODO questionnaire",
  indivID         = "uuid2",
  mixing          = TRUE,
  nCores          = 4, 
  outputDirectory = "output"
)

# ################################################################# #
#### LOAD DATA AND APPLY ANY TRANSFORMATIONS                     ####
# ################################################################# #

### Loading data from package
### if data is to be loaded from a file (e.g. called data.csv),
### the code would be: database = read.csv("data.csv",header=TRUE)
database = s12
### for data dictionary, use ?apollo_drugChoiceData

# ################################################################# #
#### DEFINE MODEL PARAMETERS                                     ####
# ################################################################# #

#ref cat strategy: don't use one that is too small and think of what you want to explore. Otherwise choose the middle or extremes.

### Vector of parameters, including any that are kept fixed in estimation
apollo_beta = c(
  sigma_error                                       = 0,
  #beta_randstad_change_randstad                    = 0,
  beta_randstad_change_notrandstad                    = 0,
  beta_randstad_change_torandstad                    = 0,
  beta_randstad_change_fromrandstad                    = 0,
  # beta_leeftijd_group_10_19               = 0,
  # beta_leeftijd_group_20_29               = 0,
  # #beta_leeftijd_group_30_39               = 0,
  # beta_leeftijd_group_40_49               = 0,
  # beta_leeftijd_group_50_59               = 0,
  # beta_leeftijd_group_60_69               = 0,
  # beta_leeftijd_group_70_79               = 0,
  # beta_leeftijd_group_80_                 = 0,
  # beta_leeftijd_group_10_29               = 0,
  # #beta_leeftijd_group_30_49               = 0,
  # beta_leeftijd_group_50_69               = 0,
  # beta_leeftijd_group_70_                 = 0,
  # #beta_huishoudensinkomen__980            = 0,
  # beta_huishoudensinkomen_980_1870        = 0,
  # beta_huishoudensinkomen_1870_2680       = 0,
  # beta_huishoudensinkomen_2680_3800       = 0,
  # beta_huishoudensinkomen_3800_5460       = 0,
  # beta_huishoudensinkomen_5460_           = 0,
  beta_huishoudensinkomen__1870           = 0,
  #beta_huishoudensinkomen_1870_3800       = 0,
  beta_huishoudensinkomen_3800_           = 0,
  #beta_nelectrischefietsen_change_2       = 0,
  beta_nelectrischefietsen_change_3       = 0,
  beta_nelectrischefietsen_change_1      = 0,
  #beta_nnormalefietsen_change_2           = 0,
  beta_nnormalefietsen_change_3           = 0,
  beta_nnormalefietsen_change_1          = 0,
  # #beta_sted_woon_nu_1                     = 0,
  # beta_sted_woon_nu_2                     = 0,
  # beta_sted_woon_nu_3                     = 0,
  # beta_sted_woon_nu_4                     = 0,
  # beta_sted_woon_nu_5                     = 0,
  # beta_sted_woon_nu_NA                    = 0,
  beta_huishoudenstype_anders             = 0,
  beta_huishoudenstype_eengezinshuishouden= 0,
  beta_huishoudenstype_eengezinshuishoudenmetkinderen    = 0,
  beta_huishoudenstype_meergezinshuishoudenmetkinderen   = 0,
  #beta_huishoudenstype_meergezinshuishoudenzonderkinderen= 0,
  beta_weekdist_woonwerk_changecat_decreasedcommute    = 0,
  beta_weekdist_woonwerk_changecat_increasedcommute    = 0,
  beta_weekdist_woonwerk_changecat_samecommute         = 0,
  #beta_weekdist_woonwerk_changecat_nojob              = 0,
  beta_weekdist_woonwerk_changecat_lostjob             = 0,
  beta_weekdist_woonwerk_changecat_gotjob              = 0,
  beta_weekdist_woonwerk_changecat_alwaysworkfromhome  = 0,
  beta_weekdist_woonwerk_changecat_workfromhometocommuting = 0,
  beta_weekdist_woonwerk_changecat_commutingtoworkfromhome = 0,
  beta_weekdist_woonwerk_changecat_differingaddresses  = 0,
  tau_nautos_change_1                = 0,
  tau_nautos_change_2                = 1)

### Vector with names (in quotes) of parameters to be kept fixed at their starting value in apollo_beta, use apollo_beta_fixed = c() if none
apollo_fixed = c()

# ################################################################# #
#### DEFINE RANDOM COMPONENTS                                    ####
# ################################################################# #

### Set parameters for generating draws
apollo_draws = list(
  interDrawsType = "sobol",
  interNDraws    = 10,
  interUnifDraws = c(),
  interNormDraws = paste0("draws_", c("error")),
  intraDrawsType = "",
  intraNDraws    = 0,
  intraUnifDraws = c(),
  intraNormDraws = c()
)

### Create random parameters
apollo_randCoeff = function(apollo_beta, apollo_inputs){
  randcoeff = list()
  
  randcoeff[["error"]]  = sigma_error*draws_error
  
  return(randcoeff)
}

# ################################################################# #
#### GROUP AND VALIDATE INPUTS                                   ####
# ################################################################# #

apollo_inputs = apollo_validateInputs()

# ################################################################# #
#### DEFINE MODEL AND LIKELIHOOD FUNCTION                        ####
# ################################################################# #

apollo_probabilities=function(apollo_beta, apollo_inputs, functionality="estimate"){
  
  ### Attach inputs and detach after function exit
  apollo_attach(apollo_beta, apollo_inputs)
  on.exit(apollo_detach(apollo_beta, apollo_inputs))
  
  ### Create list of probabilities P
  P = list()
  
  ### Calculate probabilities using Ordered Logit model
  ol_settings = list(outcomeOrdered = nautos_change,
                     utility        =
                       error +
                       beta_randstad_change_notrandstad*randstad_change_notrandstad +
                       beta_randstad_change_torandstad*randstad_change_torandstad +
                       beta_randstad_change_fromrandstad*randstad_change_fromrandstad +
                       #beta_randstad_randstad_randstad_randstad +
                       # beta_leeftijd_group_10_19*leeftijd_group_10_19 +
                       # beta_leeftijd_group_20_29*leeftijd_group_20_29 +
                       # #beta_leeftijd_group_30_39*leeftijd_group_30_39 +
                       # beta_leeftijd_group_40_49*leeftijd_group_40_49 +
                       # beta_leeftijd_group_50_59*leeftijd_group_50_59 +
                       # beta_leeftijd_group_60_69*leeftijd_group_60_69 +
                       # beta_leeftijd_group_70_79*leeftijd_group_70_79 +
                       # beta_leeftijd_group_80_*leeftijd_group_80_ +
                       # beta_leeftijd_group_10_29*leeftijd_group_10_29 +
                       # #beta_leeftijd_group_30_49*leeftijd_group_30_49 +
                     # beta_leeftijd_group_50_69*leeftijd_group_50_69 +
                     # beta_leeftijd_group_70_*leeftijd_group_70_ +
                     # #beta_huishoudensinkomen__980*huishoudensinkomen__980 +
                     # beta_huishoudensinkomen_980_1870*huishoudensinkomen_980_1870 +
                     # beta_huishoudensinkomen_1870_2680*huishoudensinkomen_1870_2680 +
                     # beta_huishoudensinkomen_2680_3800*huishoudensinkomen_2680_3800 +
                     # beta_huishoudensinkomen_3800_5460*huishoudensinkomen_3800_5460 +
                     # beta_huishoudensinkomen_5460_*huishoudensinkomen_5460_ +
                     beta_huishoudensinkomen__1870*huishoudensinkomen__1870 +
                       #beta_huishoudensinkomen_1870_3800*huishoudensinkomen_1870_3800 +
                       beta_huishoudensinkomen_3800_*huishoudensinkomen_3800_ +
                       #beta_nelectrischefietsen_change_2*nelectrischefietsen_change_2 +
                       beta_nelectrischefietsen_change_3*nelectrischefietsen_change_3 +
                       beta_nelectrischefietsen_change_1*nelectrischefietsen_change_1 +
                       #beta_nnormalefietsen_change_2*nnormalefietsen_change_2 +
                       beta_nnormalefietsen_change_3*nnormalefietsen_change_3 +
                       beta_nnormalefietsen_change_1*nnormalefietsen_change_1 +
                       # #beta_sted_woon_nu_1*sted_woon_nu_1 +
                       # beta_sted_woon_nu_2*sted_woon_nu_2 +
                       # beta_sted_woon_nu_3*sted_woon_nu_3 +
                       # beta_sted_woon_nu_4*sted_woon_nu_4 +
                       # beta_sted_woon_nu_5*sted_woon_nu_5 +
                       # beta_sted_woon_nu_NA*sted_woon_nu_NA +
                       beta_huishoudenstype_anders*huishoudenstype_anders +
                       beta_huishoudenstype_eengezinshuishouden*huishoudenstype_eengezinshuishouden +
                       beta_huishoudenstype_eengezinshuishoudenmetkinderen*huishoudenstype_eengezinshuishoudenmetkinderen +
                       beta_huishoudenstype_meergezinshuishoudenmetkinderen*huishoudenstype_meergezinshuishoudenmetkinderen +
                       #beta_huishoudenstype_meergezinshuishoudenzonderkinderen*huishoudenstype_meergezinshuishoudenzonderkinderen +
                       beta_weekdist_woonwerk_changecat_decreasedcommute*weekdist_woonwerk_changecat_decreasedcommute +
                       beta_weekdist_woonwerk_changecat_increasedcommute*weekdist_woonwerk_changecat_increasedcommute +
                       beta_weekdist_woonwerk_changecat_samecommute*weekdist_woonwerk_changecat_samecommute +
                       #beta_weekdist_woonwerk_changecat_nojob*weekdist_woonwerk_changecat_nojob +
                       beta_weekdist_woonwerk_changecat_lostjob*weekdist_woonwerk_changecat_lostjob +
                       beta_weekdist_woonwerk_changecat_gotjob*weekdist_woonwerk_changecat_gotjob +
                       beta_weekdist_woonwerk_changecat_alwaysworkfromhome*weekdist_woonwerk_changecat_alwaysworkfromhome +
                       beta_weekdist_woonwerk_changecat_workfromhometocommuting*weekdist_woonwerk_changecat_workfromhometocommuting +
                       beta_weekdist_woonwerk_changecat_commutingtoworkfromhome*weekdist_woonwerk_changecat_commutingtoworkfromhome +
                       beta_weekdist_woonwerk_changecat_differingaddresses*weekdist_woonwerk_changecat_differingaddresses,
                     tau             = list(tau_nautos_change_1, tau_nautos_change_2))
  #rows           = (task==1))
  
  P[["model"]] = apollo_ol(ol_settings, functionality)
  
  ### Take product across observation for same individual
  #P = apollo_panelProd(P, apollo_inputs, functionality)
  
  ### Prepare and return outputs of function
  P = apollo_prepareProb(P, apollo_inputs, functionality)
  return(P)
}

# ################################################################# #
#### MODEL ESTIMATION                                            ####
# ################################################################# #

model = apollo_estimate(apollo_beta, apollo_fixed, apollo_probabilities, apollo_inputs)

# ################################################################# #
#### MODEL OUTPUTS                                               ####
# ################################################################# #

# ----------------------------------------------------------------- #
#---- FORMATTED OUTPUT (TO SCREEN)                               ----
# ----------------------------------------------------------------- #

apollo_modelOutput(model)

# ----------------------------------------------------------------- #
#---- FORMATTED OUTPUT (TO FILE, using model name)               ----
# ----------------------------------------------------------------- #

apollo_saveOutput(model)
When I run it, I get this error:

Code: Select all

Pre-processing likelihood function...
Preparing workers for multithreading...

Testing influence of parametersError in checkForRemoteErrors(lapply(cl, recvResult)) : 
  4 nodes produced errors; first error: Need to average over inter-individual draws! (see ?apollo_avgInterDraws)
Seems to be a problem with the fact that I have one observation per individual. I don't know how to solve it since all the examples on the websites have multiple observations per individual.

I tried changing this section:

Code: Select all

### Set parameters for generating draws
apollo_draws = list(
  interDrawsType = "sobol",
  interNDraws    = 10,
  interUnifDraws = c(),
  interNormDraws = paste0("draws_", c("error")),
  intraDrawsType = "",
  intraNDraws    = 0,
  intraUnifDraws = c(),
  intraNormDraws = c()
)
By switching around the inter and intra values, but it gave a different error:

Code: Select all

All checks on database completed.
Error in apollo_makeDraws(apollo_inputs, silent = silent) : 
Intra-person draws are used without a panel structure. This is not allowed!
Any idea what I should do? I am trying to make a mixed ordered logit model.

Any help will be greatly appreciated, thank you!
stephanehess
Site Admin
Posts: 974
Joined: 24 Apr 2020, 16:29

Re: Error when using mixed logit with only one observation per individual

Post by stephanehess »

Hi

Apollo is trying to help you by saying

Code: Select all

Need to average over inter-individual draws!
You are missing the call to

Code: Select all

apollo_avgInterDraws
, i.e. you are estimating a mixed model without averaging over draws.

The draws are inter-individual as you only have one observation per person, so they couldn't be intra-individual

Stephane
--------------------------------
Stephane Hess
www.stephanehess.me.uk
victornielsen
Posts: 13
Joined: 19 Apr 2022, 15:49

Re: Error when using mixed logit with only one observation per individual

Post by victornielsen »

What goes into that call? And where do I add it?
stephanehess
Site Admin
Posts: 974
Joined: 24 Apr 2020, 16:29

Re: Error when using mixed logit with only one observation per individual

Post by stephanehess »

Please have a look at the mixed logit examples on the website
--------------------------------
Stephane Hess
www.stephanehess.me.uk
victornielsen
Posts: 13
Joined: 19 Apr 2022, 15:49

Re: Error when using mixed logit with only one observation per individual

Post by victornielsen »

Got it to work. Solution confirmed.
caldeiraga
Posts: 11
Joined: 24 Aug 2020, 15:07
Location: Brazil
Contact:

Re: Error when using mixed logit with only one observation per individual

Post by caldeiraga »

Hi Stephane and David,

I'm trying to estimate a mixed ordered choice model with random threshold parameters. Bellow is the code I'm using to estimate the model. I got the following message: "Error in apollo_validate(op_settings, modelType, functionality, apollo_inputs) :
Tresholds for model component "model" are not strictly increasing at starting values!".

I tried different values for the mean and sd initial values but it didn't work. I'm not using any other variable for now, just trying with the threshold parameters first. Do you have any suggestions on how I can assure tau_1 < tau_2 in this case? Thanks!

Code: Select all

apollo_initialise()

apollo_control = list(
  modelName  ="OP_model",
  indivID    ="id_pess", 
  mixing=T,
  nCores = 9)

### Set up starting values for parameters to estimate
apollo_beta <- c(
  # parameters for predictive elements
  sd_multi_1 = 0,
  gamma_multi_1 = 0,
  sd_multi_2 = 3,
  gamma_multi_2 = 3
)
# Fixed parameters, to force identification.

apollo_fixed <- c()

# Set up the form of the maximum simulated likelihood
apollo_draws <- list(
  interDrawsType = "halton",
  interNDraws = 100,
  interNormDraws = c("eta_multi_1","eta_multi_2")
)

# Set up random coefficients definitions
apollo_randCoeff <- function(apollo_beta, apollo_inputs) {
  randcoef <- list()
  randcoef[['tau_multi_1']] = gamma_multi_1 + eta_multi_1*sd_multi_1
  randcoef[['tau_multi_2']] = gamma_multi_2 + eta_multi_2*sd_multi_2
  return(randcoef)
}

### Group and validate input
apollo_inputs <- apollo_validateInputs()

### Set up the probabilities for the choices.
apollo_probabilities <- function(apollo_beta,
                                 apollo_inputs,
                                 functionality ="estimate") {

  ### Attach inputs and detach after function exit
  apollo_attach (apollo_beta, apollo_inputs)
  on.exit(apollo_detach(apollo_beta, apollo_inputs))
  
  ### Create list for probabilities
  P <- list()

  op_settings_multi <- list(outcomeOrdered = outcome1,
                            V = 0,
                            tau = list(tau_multi_1, tau_multi_2),
                            coding = 1:3)
  #
  P[['model']] <- apollo_op(op_settings_multi, functionality)
  #
  ### Average across inter-individual draws
  P <- apollo_avgInterDraws(P, apollo_inputs, functionality)
  ### Prepare and return outputs of function
  P <- apollo_prepareProb(P, apollo_inputs, functionality)

  return(P)
}

model = apollo_estimate(apollo_beta, apollo_fixed, 
                        apollo_probabilities, apollo_inputs)

apollo_modelOutput(model) 
Best regards,
Gabriel C.
stephanehess
Site Admin
Posts: 974
Joined: 24 Apr 2020, 16:29

Re: Error when using mixed logit with only one observation per individual

Post by stephanehess »

Hi

apologies for the slow response, the forum was offline due to a technical issue.

What you could do is to make the thresholds additive, where the shifts are strictly positive, e.g. using a lognormal for the shifts

Stephane
--------------------------------
Stephane Hess
www.stephanehess.me.uk
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