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引用次数: 11
摘要
2007年,美国住房和城市发展部发起了一项针对全美无家可归者的时点统计。这些统计是由连续关怀计划管理的,该计划提供了过去十年无家可归人口的空间和时间数据。不幸的是,这个行政空间单位与美国人口普查局定义的更常见的面积单位不一致,这限制了这些数据的可用性。为了统一这两个区域单位,空间分解、匹配和imputation允许将Continuum of Care数据与县数据对齐。由此产生的2005年至2017年县级无家可归者统计数据作为R包提供。县级数据的空间精度和时间变异性均高于关爱级连续体数据。非参数回归分析表明,在县域和连续关怀水平上,数据的时空变化可以很好地近似于加性时空效应。
Connecting Continuum of Care point-in-time homeless counts to United States Census areal units
ABSTRACT In 2007, the Department of Housing and Urban Development initiated a point-in-time count of the homeless across the United States. The counts are administered by the Continuum of Care Program, which provides spatial and temporal data for the homeless population over the last decade. Unfortunately, this administrative spatial unit does not align with the more common areal units defined by the United States Census Bureau, which limits usability of these data. To unify these two areal units, spatial disaggregation, matching, and imputation allow for aligning Continuum of Care data with county data. The resulting county-level homeless counts for the years 2005 to 2017 are provided as an R package. The county-level data display more spatial precision and more temporal variation than the Continuum of Care-level data. Nonparametric regression analyses reveal that the spatiotemporal variation in the data can be well approximated by additive spatial and temporal effects at both the county and Continuum of Care level.
期刊介绍:
Mathematical Population Studies publishes carefully selected research papers in the mathematical and statistical study of populations. The journal is strongly interdisciplinary and invites contributions by mathematicians, demographers, (bio)statisticians, sociologists, economists, biologists, epidemiologists, actuaries, geographers, and others who are interested in the mathematical formulation of population-related questions.
The scope covers both theoretical and empirical work. Manuscripts should be sent to Manuscript central for review. The editor-in-chief has final say on the suitability for publication.