The results from empirical data of the two Chinese trees showed that Cox regression may be weak to determine importance of critical factors because differences between factors are often too small to make a valid judgment. In addition, effects of the two factors on estimation accuracies displayed different patterns, which may vary with tree species. The results from simulated data also suggested that Cox regression may have limited use in ranking the importance of critical factors. Among the four schemes of factor combinations, the one considering both factors (the maximum) and the one not considering any (the minimum) define two extremes of a gradient of heterogeneity captured, with the one-factor schemes coming in-between. The results of the simulated data indicated that the order approach tended to be more likely to produce accurate estimates because its estimates were often closer to those of the maximum captured heterogeneity scheme than those of the diameter approach were. The results of this study highlighted the limitations to empirical data and the associated methods and, thus, the needs for simulated data in both method comparisons and significance ranking.