ASCs in RRM example
Posted: 10 Nov 2022, 10:07
I've just tried to specify my first RRM model within Apollo and everything seems fine, except for the alternative-specific constants (ASCs). The specification is based on the RRM example on the Apollo homepage. The following statement can be found in the manual on page 51:
In contrast, the MNL model:
As you can see, the estimates in the RRM model are as expected: Same signs and relative orders of magnitude, but lower absolute levels. The ASCs also look good, only the sign is "wrong".
Since the ASCs do not enter equation 5.13, shouldn't the sign be reversed in the model specficiation? Otherwise, according to my understanding, one would have to consider in the interpretation that the ASCs are regrets, i.e., a negative sign is positive and vice versa.
I did the same. The ASCs are intended to capture left-right effects. My results look like this:For the alternative specific constants (ASCs), we adopt the convention of entering them directly into the regret function rather than using Equation 5.13.
Code: Select all
Estimate s.e. t.rat.(0) p(1-sided) Rob.s.e. Rob.t.rat.(0) p(1-sided)
b_asc_1 0.033875 0.034216 0.9900 0.16108 0.034215 0.9901 0.161074
b_asc_2 -0.147582 0.032767 -4.5039 3.336e-06 0.034023 -4.3377 7.199e-06
b_asc_3 0.000000 NA NA NA NA NA NA
b_Frequency 0.007539 0.006017 1.2531 0.10509 0.008125 0.9279 0.176733
b_Duration -0.053585 0.010776 -4.9727 3.301e-07 0.013338 -4.0175 2.941e-05
b_Temperature_22 0.000000 NA NA NA NA NA NA
b_Temperature_24 -0.026134 0.013532 -1.9313 0.02673 0.015229 -1.7161 0.043073
b_Temperature_26 -0.223475 0.015105 -14.7944 0.00000 0.021716 -10.2909 0.000000
b_Temperature_27 -0.334757 0.016328 -20.5021 0.00000 0.024956 -13.4141 0.000000
b_Compensation_Company 0.000000 NA NA NA NA NA NA
b_Compensation_IceDrink 0.056305 0.014259 3.9487 3.928e-05 0.019549 2.8802 0.001987
b_Compensation_Donation -0.020718 0.014813 -1.3986 0.08096 0.021257 -0.9746 0.164871
b_Warning_None 0.000000 NA NA NA NA NA NA
b_Warning_15min 0.073235 0.014498 5.0515 2.192e-07 0.014889 4.9188 4.354e-07
b_Warning_DayBefore 0.105387 0.014232 7.4047 6.573e-14 0.015260 6.9063 2.488e-12Code: Select all
Estimate s.e. t.rat.(0) p(1-sided) Rob.s.e. Rob.t.rat.(0) p(1-sided)
b_asc_1 -0.03381 0.034225 -0.9880 0.16159 0.03423 -0.9878 0.161627
b_asc_2 0.14764 0.032775 4.5046 3.325e-06 0.03405 4.3364 7.241e-06
b_asc_3 0.00000 NA NA NA NA NA NA
b_Frequency 0.01139 0.009028 1.2617 0.10352 0.01220 0.9340 0.175157
b_Duration -0.08034 0.016205 -4.9579 3.564e-07 0.02004 -4.0088 3.052e-05
b_Temperature_22 0.00000 NA NA NA NA NA NA
b_Temperature_24 -0.07711 0.039577 -1.9482 0.02569 0.04455 -1.7306 0.041762
b_Temperature_26 -0.64854 0.042497 -15.2609 0.00000 0.06093 -10.6449 0.000000
b_Temperature_27 -0.96542 0.045042 -21.4335 0.00000 0.06865 -14.0621 0.000000
b_Compensation_Company 0.00000 NA NA NA NA NA NA
b_Compensation_IceDrink 0.14167 0.035958 3.9399 4.077e-05 0.04934 2.8715 0.002043
b_Compensation_Donation -0.05158 0.037044 -1.3925 0.08189 0.05318 -0.9700 0.166032
b_Warning_None 0.00000 NA NA NA NA NA NA
b_Warning_15min 0.18521 0.036927 5.0157 2.642e-07 0.03792 4.8847 5.179e-07
b_Warning_DayBefore 0.26722 0.036412 7.3389 1.077e-13 0.03905 6.8427 3.886e-12Since the ASCs do not enter equation 5.13, shouldn't the sign be reversed in the model specficiation? Otherwise, according to my understanding, one would have to consider in the interpretation that the ASCs are regrets, i.e., a negative sign is positive and vice versa.