I am working on an ICLV model for bicycle to work decisions that is specified as a binary choice. I am trying to incorporate 4 latent variables namely safebiking, environment, easeoftravel and lowtraffic. The measurement model consists of 12 indicator variables which I have separately established through an exploratory factor analysis.
It seems that the effects of the LVs are rather insignificant based on the t ratio. However, I am not sure if I am specifying the latent variables correctly in the model.
Hope you can check my current model at https://gist.github.com/ncctiglao/aa2d4 ... 9c4bbb3c41
Best regards,
Noriel Tiglao
Here are the model outputs:
Code: Select all
Model run by User using Apollo 0.2.8 on R 4.2.1 for Windows.
www.ApolloChoiceModelling.com
Model name : Hybrid Model for Bicycle to Work
Model description : ICLV model
Model run at : 2022-11-30 10:50:39
Estimation method : bfgs
Model diagnosis : successful convergence
Number of individuals : 519
Number of rows in database : 519
Number of modelled outcomes : 5709
indic_safebiking_1 : 519
indic_safebiking_2 : 519
indic_safebiking_3 : 519
indic_environment_1 : 519
indic_environment_2 : 519
indic_easoftravel_1 : 519
indic_easoftravel_2 : 519
indic_lowtraffic_1 : 519
indic_lowtraffic_2 : 519
indic_lowtraffic_3 : 519
biketowork : 519
Number of cores used : 4
Number of inter-individual draws : 100 (halton)
WARNING: Inter-individual draws were used
without a panel data structure.
LL(start) : -7173.31
LL (whole model) at equal shares, LL(0) : Not applicable
LL (whole model) at observed shares, LL(C) : Not applicable
LL(final, whole model) : -3063.91
Rho-squared vs equal shares : Not applicable
Adj.Rho-squared vs equal shares : Not applicable
Rho-squared vs observed shares : Not applicable
Adj.Rho-squared vs observed shares : Not applicable
AIC : 6191.81
BIC : 6327.87
LL(0,indic_safebiking_1) : Not applicable
LL(final,indic_safebiking_1) : -276.69
LL(0,indic_safebiking_2) : Not applicable
LL(final,indic_safebiking_2) : -261.8
LL(0,indic_safebiking_3) : Not applicable
LL(final,indic_safebiking_3) : -239.68
LL(0,indic_environment_1) : Not applicable
LL(final,indic_environment_1) : -311.07
LL(0,indic_environment_2) : Not applicable
LL(final,indic_environment_2) : -337.84
LL(0,indic_easeoftravel_1) : Not applicable
LL(final,indic_easeoftravel_1) : -276.03
LL(0,indic_easeoftravel_2) : Not applicable
LL(final,indic_easeoftravel_2) : -304.06
LL(0,indic_lowtraffic_1) : Not applicable
LL(final,indic_lowtraffic_1) : -302.58
LL(0,indic_lowtraffic_2) : Not applicable
LL(final,indic_lowtraffic_2) : -276.16
LL(0,indic_lowtraffic_3) : Not applicable
LL(final,indic_lowtraffic_3) : -343.2
LL(0,biketowork) : -359.74
LL(final,biketowork) : -276.98
Estimated parameters : 32
Time taken (hh:mm:ss) : 00:02:23.62
pre-estimation : 00:00:22.76
estimation : 00:00:23.4
post-estimation : 00:01:37.46
Iterations : 55
Min abs eigenvalue of Hessian : 0.570972
Unconstrained optimisation.
These outputs have had the scaling used in estimation applied to them.
Estimates:
Estimate s.e. t.rat.(0) Rob.s.e. Rob.t.rat.(0)
asc_yes 0.881703 1.310166 0.67297 1.266522 0.69616
b_age -0.006531 0.001337 -4.88497 0.001546 -4.22463
b_gender 0.055327 0.038335 1.44325 0.051166 1.08134
b_income -0.050709 0.093310 -0.54345 0.096981 -0.52288
b_hhead -0.015020 0.218529 -0.06873 0.212138 -0.07080
b_educ -0.033341 0.165516 -0.20144 0.161943 -0.20588
b_bikeown 0.228399 0.049211 4.64122 0.056987 4.00791
b_sector -0.537038 0.247046 -2.17383 0.245567 -2.18693
lambda_safebiking 0.169389 0.146053 1.15978 0.159044 1.06505
lambda_environment -0.150562 0.129317 -1.16428 0.142029 -1.06007
lambda_easeoftravel 0.095543 0.149451 0.63929 0.177227 0.53910
lambda_lowtraffic 0.096464 0.144866 0.66589 0.148429 0.64990
gamma_bikelane 0.417917 0.016173 25.84050 0.019556 21.36980
gamma_pavement 0.419824 0.015004 27.98032 0.014935 28.10931
gamma_safety 0.420632 0.014614 28.78219 0.016087 26.14697
gamma_scenery 0.521763 0.019359 26.95217 0.024631 21.18285
gamma_shade 0.466516 0.021027 22.18600 0.024664 18.91473
gamma_shorttime 0.510761 0.019248 26.53647 0.026065 19.59600
gamma_shortestdist 0.491107 0.021110 23.26433 0.030557 16.07168
gamma_lesstraffic 0.408475 0.017942 22.76691 0.019754 20.67800
gamma_slowvehspeed 0.453849 0.018130 25.03262 0.021872 20.75067
gamma_resstreet 0.451214 0.020048 22.50623 0.022597 19.96764
sigma_bikelane 0.337446 0.015187 22.21926 0.030714 10.98656
sigma_pavement 0.318022 0.014153 22.47059 0.021745 14.62478
sigma_safety 0.282339 0.015179 18.60009 0.028665 9.84967
sigma_scenery 0.278361 0.037766 7.37068 0.050004 5.56676
sigma_shade 0.391462 0.026907 14.54896 0.039093 10.01354
sigma_shorttime 0.247070 0.025193 9.80699 0.026593 9.29090
sigma_shortestdist 0.324231 0.021698 14.94258 0.033897 9.56524
sigma_lesstraffic 0.380826 0.015691 24.27021 0.026708 14.25872
sigma_slowvehspeed 0.316406 0.017595 17.98298 0.025051 12.63039
sigma_resstreet 0.421170 0.017501 24.06589 0.023969 17.57129