clogit matching

Scripts/clogit/predictions/clogit_wtp_space_pred_macthing.R

+#### Apollo standard script #####
+
+
+data_predictions <- readRDS("Data/predictions.RDS")
+
+database <- left_join(database_full, data_predictions, by="id")
+
+
+
+database <- database %>% 
+  filter(!is.na(Treatment_new)) %>%
+  mutate(Dummy_Treated = case_when(Treatment_new == 1|Treatment_new == 2  ~ 1, TRUE ~ 0),
+         Dummy_Vol_Treated = case_when(Treatment_new == 5 |Treatment_new == 4 ~ 1, TRUE ~ 0),
+         Dummy_no_info = case_when(Treatment_new == 3 ~ 1, TRUE~0)) %>% 
+  mutate(Dummy_Treated_Pred = case_when(Dummy_Treated == 1 & PredictedGroup == 1 ~1, TRUE~0),
+         Dummy_Treated_Not_Pred = case_when(Dummy_Treated == 1 & PredictedGroup == 0 ~1, TRUE~0)) %>% 
+  mutate(Dummy_Control_Not_Pred = case_when(Treatment_new == 6 & PredictedGroup == 0 ~1, TRUE~0))
+
+
+
+
+#initialize model 
+
+apollo_initialise()
+
+
+### Set core controls
+apollo_control = list(
+  modelName  = "clogit_wtp_Prediction_matching",
+  modelDescr = "clogit wtp space Prediction matching",
+  indivID    ="id",
+  mixing     = FALSE,
+  HB= FALSE,
+  nCores     = n_cores, 
+  outputDirectory = "Estimation_results/clogit/prediction"
+)
+
+##### Define model parameters depending on your attributes and model specification! ####
+# set values to 0 for conditional logit model
+
+apollo_beta=c(b_natural = 15,
+              b_walking = -1,
+              b_rent = 0,
+              b_ASC_sq = 0,
+              b_ASC_sq_opt_yes= 0,
+              b_ASC_sq_opt_no= 0,
+              b_ASC_sq_treat_pred = 0,
+              b_ASC_sq_treat_not_pred = 0,
+              b_ASC_sq_control_not_pred = 0,
+              b_nat_opt_yes= 0,
+              b_nat_opt_no= 0,
+              b_nat_treat_pred = 0,
+              b_nat_treat_not_pred = 0,
+              b_nat_control_not_pred = 0,
+              b_walking_opt_yes= 0,
+              b_walking_opt_no = 0,
+              b_walking_treat_pred = 0,
+              b_walking_treat_not_pred = 0,
+              b_walking_control_not_pred = 0,
+              b_rent_opt_yes = 0,
+              b_rent_opt_no = 0,
+              b_rent_treat_pred = 0,
+              b_rent_treat_not_pred = 0,
+              b_rent_control_not_pred = 0
+)
+
+### specify parameters that should be kept fixed, here = none
+apollo_fixed = c()
+
+
+### validate 
+apollo_inputs = apollo_validateInputs()
+apollo_probabilities=function(apollo_beta, apollo_inputs, functionality="estimate"){
+  
+  ### Function initialisation: do not change the following three commands
+  ### 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()
+  
+  #### List of utilities (later integrated in mnl_settings below)  ####
+  # Define utility functions here:
+  
+  V = list()
+  V[['alt1']] = -(b_rent + b_rent_opt_yes * Dummy_Vol_Treated + b_rent_opt_no * Dummy_no_info + b_rent_treat_pred * Dummy_Treated_Pred +
+                    b_rent_treat_not_pred * Dummy_Treated_Not_Pred + b_rent_control_not_pred * Dummy_Control_Not_Pred)*
+    (b_natural*Naturalness_1 + b_walking*WalkingDistance_1 
+     + b_nat_opt_yes * Dummy_Vol_Treated * Naturalness_1 + b_nat_opt_no * Dummy_no_info * Naturalness_1
+     + b_nat_treat_pred * Dummy_Treated_Pred * Naturalness_1 + b_nat_treat_not_pred * Dummy_Treated_Not_Pred * Naturalness_1 + b_nat_control_not_pred * Dummy_Control_Not_Pred * Naturalness_1
+     + b_walking_opt_yes * Dummy_Vol_Treated * WalkingDistance_1 + b_walking_opt_no* Dummy_no_info * WalkingDistance_1
+     + b_walking_treat_pred * Dummy_Treated_Pred * WalkingDistance_1 + b_walking_treat_not_pred * Dummy_Treated_Not_Pred * WalkingDistance_1 + b_walking_control_not_pred * Dummy_Control_Not_Pred * WalkingDistance_1
+     - Rent_1)
+  
+  V[['alt2']] =  -(b_rent + b_rent_opt_yes * Dummy_Vol_Treated + b_rent_opt_no * Dummy_no_info + b_rent_treat_pred * Dummy_Treated_Pred +
+                     b_rent_treat_not_pred * Dummy_Treated_Not_Pred + b_rent_control_not_pred * Dummy_Control_Not_Pred)*
+    (b_natural*Naturalness_2 + b_walking*WalkingDistance_2 
+     + b_nat_opt_yes * Dummy_Vol_Treated * Naturalness_2 + b_nat_opt_no  * Dummy_no_info * Naturalness_2
+     + b_nat_treat_pred * Dummy_Treated_Pred * Naturalness_2 + b_nat_treat_not_pred * Dummy_Treated_Not_Pred * Naturalness_2 + b_nat_control_not_pred * Dummy_Control_Not_Pred * Naturalness_2
+     + b_walking_opt_yes * Dummy_Vol_Treated * WalkingDistance_2 + b_walking_opt_no* Dummy_no_info * WalkingDistance_2
+     + b_walking_treat_pred * Dummy_Treated_Pred * WalkingDistance_2 + b_walking_treat_not_pred * Dummy_Treated_Not_Pred * WalkingDistance_2 + b_walking_control_not_pred * Dummy_Control_Not_Pred * WalkingDistance_2
+     - Rent_2)
+  
+  V[['alt3']] =  -(b_rent + b_rent_opt_yes * Dummy_Vol_Treated + b_rent_opt_no * Dummy_no_info + b_rent_treat_pred * Dummy_Treated_Pred +
+                     b_rent_treat_not_pred * Dummy_Treated_Not_Pred + b_rent_control_not_pred * Dummy_Control_Not_Pred)*
+    (b_natural*Naturalness_3 + b_walking*WalkingDistance_3 
+     + b_nat_opt_yes * Dummy_Vol_Treated * Naturalness_3 + b_nat_opt_no * Dummy_no_info * Naturalness_3
+     + b_nat_treat_pred * Dummy_Treated_Pred * Naturalness_3 + b_nat_treat_not_pred * Dummy_Treated_Not_Pred * Naturalness_3 + b_nat_control_not_pred * Dummy_Control_Not_Pred * Naturalness_3
+     + b_walking_opt_yes * Dummy_Vol_Treated * WalkingDistance_3 + b_walking_opt_no* Dummy_no_info * WalkingDistance_3
+     + b_walking_treat_pred * Dummy_Treated_Pred * WalkingDistance_3 + b_walking_treat_not_pred * Dummy_Treated_Not_Pred * WalkingDistance_3 + b_walking_control_not_pred * Dummy_Control_Not_Pred * WalkingDistance_3
+     + b_ASC_sq + b_ASC_sq_opt_yes * Dummy_Vol_Treated + b_ASC_sq_opt_no * Dummy_no_info
+     + b_ASC_sq_treat_pred * Dummy_Treated_Pred + b_ASC_sq_treat_not_pred * Dummy_Treated_Not_Pred + b_ASC_sq_control_not_pred * Dummy_Control_Not_Pred - Rent_3)
+  
+  
+  ### Define settings for MNL model component
+  mnl_settings = list(
+    alternatives  = c(alt1=1, alt2=2, alt3=3),
+    avail         = 1, # all alternatives are available in every choice
+    choiceVar     = choice,
+    V             = V#,  # tell function to use list vector defined above
+    
+  )
+  
+  ### Compute probabilities using MNL model
+  P[['model']] = apollo_mnl(mnl_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                                            ##
+# ################################################################# #
+# estimate model with bfgs algorithm
+
+clogit_wtp_matching_1 = apollo_estimate(apollo_beta, apollo_fixed,
+                                                   apollo_probabilities, apollo_inputs, 
+                                                   estimate_settings=list(maxIterations=400,
+                                                                          estimationRoutine="bfgs",
+                                                                          hessianRoutine="analytic"))
+
+
+
+# ################################################################# #
+#### MODEL OUTPUTS                                               ##
+# ################################################################# #
+apollo_saveOutput(clogit_wtp_matching_1)
+apollo_modelOutput(clogit_wtp_matching_1)
+

Scripts/clogit/predictions/clogit_wtp_space_pred_macthing_complete.R

+#### Apollo standard script #####
+
+library(apollo) # Load apollo package 
+
+data_predictions1 <- readRDS("Data/predictions.RDS")
+data_predictions2 <- readRDS("Data/predictions_labeled.RDS")
+
+data_predictions <- bind_rows(data_predictions1, data_predictions2)
+
+database <- left_join(database_full, data_predictions, by="id")
+
+
+
+database <- database %>% 
+  filter(!is.na(Treatment_new)) %>%
+  mutate(Dummy_Treated = case_when(Treatment_new == 1|Treatment_new == 2  ~ 1, TRUE ~ 0),
+         Dummy_Vol_Treated = case_when(Treatment_new == 5 |Treatment_new == 4 ~ 1, TRUE ~ 0),
+         Dummy_no_info = case_when(Treatment_new == 3 ~ 1, TRUE~0)) %>% 
+  mutate(Dummy_Treated_Pred = case_when(Dummy_Treated == 1 & PredictedGroup == 1 ~1, TRUE~0),
+         Dummy_Treated_Not_Pred = case_when(Dummy_Treated == 1 & PredictedGroup == 0 ~1, TRUE~0)) %>% 
+  mutate(Dummy_Control_Not_Pred = case_when(Treatment_new == 6 & PredictedGroup == 0 ~1, TRUE~0),
+         Dummy_Opt_Treat_Pred = case_when(Treatment_A == "Vol_Treated" & PredictedGroup == 1 ~1, TRUE~0),
+         Dummy_Opt_Treat_Not_Pred = case_when(Treatment_A == "Vol_Treated" & PredictedGroup == 0 ~1, TRUE~0))
+
+
+
+#initialize model 
+
+apollo_initialise()
+
+
+### Set core controls
+apollo_control = list(
+  modelName  = "clogit_wtp_Prediction matching all complete",
+  modelDescr = "clogit wtp space Prediction matching all complete",
+  indivID    ="id",
+  mixing     = FALSE,
+  HB= FALSE,
+  nCores     = n_cores, 
+  outputDirectory = "Estimation_results/clogit/prediction"
+)
+
+##### Define model parameters depending on your attributes and model specification! ####
+# set values to 0 for conditional logit model
+
+apollo_beta=c(b_natural = 15,
+              b_walking = -1,
+              b_rent = 0,
+              b_ASC_sq = 0,
+              b_ASC_sq_opt_treated_pred = 0,
+              b_ASC_sq_opt_treated_not_pred = 0,
+              b_ASC_sq_treat_pred = 0,
+              b_ASC_sq_treat_not_pred = 0,
+              b_ASC_sq_control_not_pred = 0,
+              b_nat_opt_treated_pred = 0,
+              b_nat_opt_treated_not_pred = 0,
+              b_nat_treat_pred = 0,
+              b_nat_treat_not_pred = 0,
+              b_nat_control_not_pred = 0,
+              b_walking_opt_treated_pred = 0,
+              b_walking_opt_treated_not_pred = 0,
+              b_walking_treat_pred = 0,
+              b_walking_treat_not_pred = 0,
+              b_walking_control_not_pred = 0,
+              b_rent_opt_treated_pred = 0,
+              b_rent_opt_treated_not_pred = 0,
+              b_rent_treat_pred = 0,
+              b_rent_treat_not_pred = 0,
+              b_rent_control_not_pred = 0
+              )
+
+### specify parameters that should be kept fixed, here = none
+apollo_fixed = c()
+
+
+### validate 
+apollo_inputs = apollo_validateInputs()
+apollo_probabilities=function(apollo_beta, apollo_inputs, functionality="estimate"){
+  
+  ### Function initialisation: do not change the following three commands
+  ### 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()
+  
+  #### List of utilities (later integrated in mnl_settings below)  ####
+  # Define utility functions here:
+  
+  V = list()
+  V[['alt1']] = -(b_rent + b_rent_opt_treated_pred * Dummy_Opt_Treat_Pred + b_rent_opt_treated_not_pred * Dummy_Opt_Treat_Not_Pred + b_rent_treat_pred * Dummy_Treated_Pred +
+                    b_rent_treat_not_pred * Dummy_Treated_Not_Pred + b_rent_control_not_pred * Dummy_Control_Not_Pred)*
+    (b_natural*Naturalness_1 + b_walking*WalkingDistance_1 
+     + b_nat_opt_treated_pred * Dummy_Opt_Treat_Pred * Naturalness_1 + b_nat_opt_treated_not_pred * Dummy_Opt_Treat_Not_Pred * Naturalness_1
+     + b_nat_treat_pred * Dummy_Treated_Pred * Naturalness_1 + b_nat_treat_not_pred * Dummy_Treated_Not_Pred * Naturalness_1 + b_nat_control_not_pred * Dummy_Control_Not_Pred * Naturalness_1
+     + b_walking_opt_treated_pred * Dummy_Opt_Treat_Pred * WalkingDistance_1 + b_walking_opt_treated_not_pred* Dummy_Opt_Treat_Not_Pred * WalkingDistance_1
+     + b_walking_treat_pred * Dummy_Treated_Pred * WalkingDistance_1 + b_walking_treat_not_pred * Dummy_Treated_Not_Pred * WalkingDistance_1 + b_walking_control_not_pred * Dummy_Control_Not_Pred * WalkingDistance_1
+     - Rent_1)
+  
+  V[['alt2']] =  -(b_rent + b_rent_opt_treated_pred * Dummy_Opt_Treat_Pred + b_rent_opt_treated_not_pred * Dummy_Opt_Treat_Not_Pred + b_rent_treat_pred * Dummy_Treated_Pred +
+                     b_rent_treat_not_pred * Dummy_Treated_Not_Pred + b_rent_control_not_pred * Dummy_Control_Not_Pred)*
+    (b_natural*Naturalness_2 + b_walking*WalkingDistance_2 
+     + b_nat_opt_treated_pred * Dummy_Opt_Treat_Pred * Naturalness_2 + b_nat_opt_treated_not_pred * Dummy_Opt_Treat_Not_Pred * Naturalness_2
+     + b_nat_treat_pred * Dummy_Treated_Pred * Naturalness_2 + b_nat_treat_not_pred * Dummy_Treated_Not_Pred * Naturalness_2 + b_nat_control_not_pred * Dummy_Control_Not_Pred * Naturalness_2
+     + b_walking_opt_treated_pred * Dummy_Opt_Treat_Pred * WalkingDistance_2 + b_walking_opt_treated_not_pred* Dummy_Opt_Treat_Not_Pred * WalkingDistance_2
+     + b_walking_treat_pred * Dummy_Treated_Pred * WalkingDistance_2 + b_walking_treat_not_pred * Dummy_Treated_Not_Pred * WalkingDistance_2 + b_walking_control_not_pred * Dummy_Control_Not_Pred * WalkingDistance_2
+     - Rent_2)
+  
+  V[['alt3']] =  -(b_rent + b_rent_opt_treated_pred * Dummy_Opt_Treat_Pred + b_rent_opt_treated_not_pred * Dummy_Opt_Treat_Not_Pred + b_rent_treat_pred * Dummy_Treated_Pred +
+                     b_rent_treat_not_pred * Dummy_Treated_Not_Pred + b_rent_control_not_pred * Dummy_Control_Not_Pred)*
+    (b_natural*Naturalness_3 + b_walking*WalkingDistance_3 
+     + b_nat_opt_treated_pred * Dummy_Opt_Treat_Pred * Naturalness_3 + b_nat_opt_treated_not_pred * Dummy_Opt_Treat_Not_Pred * Naturalness_3
+     + b_nat_treat_pred * Dummy_Treated_Pred * Naturalness_3 + b_nat_treat_not_pred * Dummy_Treated_Not_Pred * Naturalness_3 + b_nat_control_not_pred * Dummy_Control_Not_Pred * Naturalness_3
+     + b_walking_opt_treated_pred * Dummy_Opt_Treat_Pred * WalkingDistance_3 + b_walking_opt_treated_not_pred* Dummy_Opt_Treat_Not_Pred * WalkingDistance_3
+     + b_walking_treat_pred * Dummy_Treated_Pred * WalkingDistance_3 + b_walking_treat_not_pred * Dummy_Treated_Not_Pred * WalkingDistance_3 + b_walking_control_not_pred * Dummy_Control_Not_Pred * WalkingDistance_3
+     + b_ASC_sq + b_ASC_sq_opt_treated_pred * Dummy_Opt_Treat_Pred + b_ASC_sq_opt_treated_not_pred * Dummy_Opt_Treat_Not_Pred
+     + b_ASC_sq_treat_pred * Dummy_Treated_Pred + b_ASC_sq_treat_not_pred * Dummy_Treated_Not_Pred + b_ASC_sq_control_not_pred * Dummy_Control_Not_Pred - Rent_3)
+  
+  
+  ### Define settings for MNL model component
+  mnl_settings = list(
+    alternatives  = c(alt1=1, alt2=2, alt3=3),
+    avail         = 1, # all alternatives are available in every choice
+    choiceVar     = choice,
+    V             = V#,  # tell function to use list vector defined above
+    
+  )
+  
+  ### Compute probabilities using MNL model
+  P[['model']] = apollo_mnl(mnl_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                                            ##
+# ################################################################# #
+# estimate model with bfgs algorithm
+
+clogit_wtp_matching_all_complete = apollo_estimate(apollo_beta, apollo_fixed,
+                                                apollo_probabilities, apollo_inputs, 
+                                                estimate_settings=list(maxIterations=400,
+                                                                       estimationRoutine="bfgs",
+                                                                       hessianRoutine="analytic"))
+
+
+
+# ################################################################# #
+#### MODEL OUTPUTS                                               ##
+# ################################################################# #
+apollo_saveOutput(clogit_wtp_matching_all_complete)
+apollo_modelOutput(clogit_wtp_matching_all_complete)
+