Scenario 1c: Additive model (misspecified)
   θ(0)=0.35
Bias CMLE 0.099 0.248 0.078 0.096
MLE 0.100 0.250 0.078 0.095
PCL 0.001 0.137 0.000 0.103
RMSE CMLE 0.179 0.287 0.168 0.184
MLE 0.157 0.277 0.145 0.158
PCL 0.139 0.188 0.131 0.168
Scenario 1c: Model with second-order contrasts
   θ(0)=0.35
Bias CMLE 0.090 0.023 0.022 0.371
MLE 0.080 0.016 0.02 0.363
PCL 0.015 0.012 0.004 0.001
RMSE CMLE 0.224 0.256 0.25 0.447
MLE 0.191 0.219 0.217 0.419
PCL 0.211 0.266 0.272 0.248
Table 3: Simulation results for the complete-case MLE, the MLE, and the pseudoconditional likelihood method. Here RMSE represents root mean squared error. The results were based on 2,000 runs. There were 2×2×2 = 8 disease subtypes. The model for the intercepts was misspecified. The missingness probabilities depend on the covariate. This is Scenario 1c, where the true values of some of the second-order contrasts of the log-odds ratio parameters were not zero.