In order to examine the relative ef

In order to examine the relative effect of the explanatory variables included in the model, the type III analyses
were performed for different correlation structures and for each variable as shown in Table 1. For example, the
type III chi-square value for the variable Precipitation is the difference between the generalized score statistic forthe model with all the variables included and the generalized score statistic for the model with the variable
Precipitation excluded. The hypothesis tested in this case is the significance of the variable Precipitation given
that all the other variables are in the model (i.e., it tests the additional contribution of Precipitation). The small pvalue
for Precipitation indicates that the effect of this variable is highly significant. Based on the p-value of type
III analysis, the effects of causative factor are assessed for disability incidents and crash incidents respectively as
followed.

結果 (繁體中文) 2:

為了檢查包含在模型中的解釋變量的相對影響，III型分析
進行對於不同的相關結構和每個變量如表1所示。例如
，III 型卡方值的變量降水與所有包含變量和廣義分數統計的模型變量廣義得分統計之間的差異滿心歡喜模式
降水排除。在這種情況下測試的假設是考慮到降水變化不定的意義
，所有其他變量都在模型（即，它測試降水的額外貢獻）。小P值
降水量表示此變量的效果是非常顯著。基於類型的p值
III分析，致病因素的作用，分別評定為傷殘事故和碰撞事故的
接踵而至。

結果 (繁體中文) 3:

為了檢驗模型中包含的解釋變數的相對影響，對不同的相關結構進行了類型分析，並為每個變數如錶1所示。舉例來說，變數降水類型的卡方值為模型中的廣義得分統計與各變數之間的差异，並對模型進行了廣義的得分統計。在這種情況下測試的假設是可變的沉澱的意義，給出的所有其他變數是在模型中（即，它測試的額外貢獻的降水。降水的小P
表明這個變數有顯著影響。基於
III型分析的P值，致病因數的影響進行評估的傷殘事故和撞車事故分別為

緊隨其後。