摘要
Considering both the discrete and ordered nature of the household car ownership an ordered logistic regression model to predict household car ownership is established by using the data of Nanjing Household Travel Survey in the year 2012. The model results show that some household characteristics such as the number of driver licenses household income and home location are significant.Yet the intersection density indicating the street patterns of home location and the dummy near the subway and the bus stop density indicating the transit accessibility of home location are insignificant.The model estimation obtains a good γ2 the goodness of fit of the model and the model validation also shows a good performance in prediction.The marginal effects of all the significant explanatory variables are calculated to quantify the odds change in the household car ownership following a one-unit change in the explanatory variables.
基于南京市2012年居民出行调查数据,建立了能同时考虑家庭小汽车拥有量的离散属性和序次属性的序次logistic回归模型,对家庭小汽车拥有量进行预测.模型结果表明:一些家庭属性比如家庭驾照持有数量、收入水平和居住位置对家庭小汽车拥有量有显著的影响,而表征家庭所在社区街道模式的变量(交叉口密度)和表征家庭所在社区公共交通可达性的变量(是否在地铁站步行范围内及公共交通站点密度)对家庭小汽车拥有量的影响并不显著.模型总体拟合度γ2和模型检验结果均表明该模型总体表现良好.最后计算了所有显著的解释变量的边际效应,即解释变量1个单位变化能够引起的家庭小汽车拥有量概率的变化.
