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Small area estimates of daily person-miles of travel: 2001 National Household Transportation Survey

机译:小面积每日旅行的人-英里的估计:2001年全国家庭运输调查

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摘要

The National Household Transportation Survey (NHTS) was designed at the national level, and for most states it does not have a large enough sample to produce reliable estimates, especially for subdomains (e.g., age groups) within a state. Using the 2001 NHTS, we produced small area estimates (SAEs) of the percentage of persons among four age groups (17 or younger, 18-39, 40-54, and 55 or older) having high daily person-miles of travel (more than 87.5 miles a day, which is the 90th percentile for daily person-miles traveled) and associated prediction intervals for all 50 states and the District of Columbia. The survey weighted hierarchical Bayes (Folsom et al., Proc of the Sect on Surv Res Methods of the Am Stat Assoc 371-375, 1999) small area estimation (SAE) methodology was used to produce state-level SAEs. This paper describes the methodology and shows that SAE can be an effective technique for producing reliable state-level estimates from large, national surveys like the NHTS. In particular, the prediction interval relative widths for SAEs were, on average, 31-48% narrower than the corresponding design-based confidence interval widths, whereas for small states the reduction was around 47-63%.
机译:全国家庭运输调查(NHTS)是在国家一级设计的,对于大多数州来说,它没有足够大的样本来提供可靠的估计,尤其是对于一个州内的子域(例如年龄组)而言。使用2001年的NHTS,我们对每天旅行的人均英里数较高的四个年龄段(17岁以下,18-39岁,40-54岁和55岁以上)的人口百分比进行了小范围估算(SAE)。超过每天87.5英里,这是每天旅行的人英里的90%)以及所有50个州和哥伦比亚特区的相关预测间隔。使用调查加权层次贝叶斯方法(Folsom等人,Am Stat Assoc 371-375上的Surv Res方法学的过程,1999年)小面积估计(SAE)方法来产生州级SAE。本文介绍了该方法,并表明SAE是一种有效的技术,可以从大型国家调查(如NHTS)中获得可靠的州级估算。特别是,SAE的预测间隔相对宽度平均比相应的基于设计的置信区间宽度窄31-48%,而对于小状态,减小幅度约为47-63%。

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