The MDC Procedure
Example 24.7 Likelihood Ratio Test
(View the complete code for this example.)
This example is an extension of Example 24.6 and uses the same data.[4] It performs another specification test, the likelihood ratio test (LR). Suppose you are interested in testing whether the nested logit model (Figure 24.30) with three subgroups that represent commuters who arrive early, on time, and late is more appropriate than the standard multinomial logit. This can be done by adding the TEST statement to the model as follows:
/*-- Restricted Model with Inclusive Value Parameters
Constrained to One --*/
proc mdc data=small maxit=200 outest=a;
model decision = r15 r10 ttime ttime_cp sde sde_cp
sdl sdlx d2l /
type=nlogit
choice=(alt);
id id;
utility u(1, ) = r15 r10 ttime ttime_cp sde sde_cp
sdl sdlx d2l;
nest level(1) = (1 2 3 4 5 6 7 8 @ 1, 9 @ 2, 10 11 12 @ 3),
level(2) = (1 2 3 @ 1);
test INC_L2G1C1=1, INC_L2G1C2=1, INC_L2G1C3=1 /LR;
run;
Output 24.7.1: Likelihood Ratio Test
Based on this test, you can conclude that the inclusive values, INC_L2G1C1, INC_L2G1C2, and INC_L2G1C3 are jointly statistically different from the value 1 at the 5% level and therefore the nested logit is a more appropriate model. The LR test can be used to test other types of restrictions in the nested logit setting as long as one model can be nested within another.
[4] These data were provided by Professor Kenneth Small. They were collected for the urban travel demand forecasting project, which was carried out by McFadden, Talvitie, and Associates (1977). The project was supported by the National Science Foundation, Research Applied to National Needs Program, through grants GI-43740 and APR74-20392 and by the Alfred P. Sloan Foundation through grant 74-21-8.