Statistical Modeling Strategy
deaths, death, tumor
TUMOR GROWTH, TUMOR
Concerning the modeling strategy of the mixed model, the final model was the model with a change of slope at week 4 and random effects on the intercept and the two slopes (The estimates of the treatment effect by subtypes and doses with three different models (piecewise linear mixed model with one-level random effects, piecewise linear mixed model with two-level random effects and joint model with one-level random effects) are summarized in Estimation of treatment effect on tumor growth (log(mmAlthough it is preferable to take into account all levels of correlation (PDX and mouse), mixed models taking into account only the mouse level correlation (one-level, AIC: 1606.1) gave very similar results to mixed models including also the PDX level correlation (two-level, AIC: 1458.7).The estimates obtained by joint model under the assumption of MNAR dropout due to death differed substantially from those obtained by the mixed models under the assumption of MAR dropout, especially in the second period when the number of deaths was increasing (Furthermore, to confirm that this difference in estimation between the mixed model and the joint model is due to the nature of the deaths, a complementary analysis was performed by perturbating the MAR data process. In the case of MCT and a MAR missing data process on tumor growth, this process can become MNAR by artificially rendering unobserved the tumor values that gave rise to the sacrifice (considering only the tumor volume measurements at an earlier stage than the ethical threshold, 900 mm