利用土地利用滤波技术对城市环境中的集体效能进行非稳态空间预测。

IF 1.3 4区 数学 Q2 STATISTICS & PROBABILITY Annals of Applied Statistics Pub Date : 2024-03-01 Epub Date: 2024-01-31 DOI:10.1214/23-aoas1813
J Brandon Carter, Christopher R Browning, Bethany Boettner, Nicolo Pinchak, Catherine A Calder
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引用次数: 0

摘要

集体效能--社区为实现其共同目标而施加社会控制的能力--是城市社会学和邻里效应文献中的一个基本概念。传统上,对集体效能的实证研究使用大样本调查来估算城市环境中不同社区的集体效能。此类研究表明,集体效能与社区暴力、教育成就和健康状况的地方差异之间存在关联。与传统的集体效能测量策略不同,"情境中的青少年健康与发展(AHDC)研究 "采用了一种新方法,从居住在俄亥俄州哥伦布市的代表性样本中获取空间参照、基于地点的集体效能评分。在本文中,我们介绍了一种新的非平稳空间模型,用于对整个研究区域的 AHDC 集体效能评分进行插值,该模型利用了有关土地利用的行政数据。我们的建设性模型规范策略包括对潜在空间过程进行维度扩展,并使用由研究区域的土地使用分区定义的过滤器,将潜在的多元空间过程与观察到的集体效能顺序评分联系起来。对参数的可识别性、模型拟合的 MCMC 算法的计算效率以及集体效能的精细空间预测等问题进行了仔细考虑。
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LAND-USE FILTERING FOR NONSTATIONARY SPATIAL PREDICTION OF COLLECTIVE EFFICACY IN AN URBAN ENVIRONMENT.

Collective efficacy-the capacity of communities to exert social control toward the realization of their shared goals-is a foundational concept in the urban sociology and neighborhood effects literature. Traditionally, empirical studies of collective efficacy use large sample surveys to estimate collective efficacy of different neighborhoods within an urban setting. Such studies have demonstrated an association between collective efficacy and local variation in community violence, educational achievement, and health. Unlike traditional collective efficacy measurement strategies, the Adolescent Health and Development in Context (AHDC) Study implemented a new approach, obtaining spatially-referenced, place-based ratings of collective efficacy from a representative sample of individuals residing in Columbus, OH. In this paper we introduce a novel nonstationary spatial model for interpolation of the AHDC collective efficacy ratings across the study area, which leverages administrative data on land use. Our constructive model specification strategy involves dimension expansion of a latent spatial process and the use of a filter defined by the land-use partition of the study region to connect the latent multivariate spatial process to the observed ordinal ratings of collective efficacy. Careful consideration is given to the issues of parameter identifiability, computational efficiency of an MCMC algorithm for model fitting, and fine-scale spatial prediction of collective efficacy.

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来源期刊
Annals of Applied Statistics
Annals of Applied Statistics 社会科学-统计学与概率论
CiteScore
3.10
自引率
5.60%
发文量
131
审稿时长
6-12 weeks
期刊介绍: Statistical research spans an enormous range from direct subject-matter collaborations to pure mathematical theory. The Annals of Applied Statistics, the newest journal from the IMS, is aimed at papers in the applied half of this range. Published quarterly in both print and electronic form, our goal is to provide a timely and unified forum for all areas of applied statistics.
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