Developing a Locally Adaptive Spatial Multilevel Logistic Model to Analyze Ecological Effects on Health Using Individual Census Records

doi:10.1080/24694452.2019.1644990

	Developing a Locally Adaptive Spatial Multilevel Logistic Model to Analyze Ecological Effects on Health Using Individual Census Records
	Dong, Guanpeng 4,5,6; Ma, Jing 7; Lee, Duncan 8; Chen, Mingxing 2; Pryce, Gwilym 3; Chen, Yu 1
刊名	ANNALS OF THE AMERICAN ASSOCIATION OF GEOGRAPHERS
	2019-09-18
页码	19
ISSN号	2469-4452
DOI	10.1080/24694452.2019.1644990
通讯作者	Dong, Guanpeng(guanpeng.dong@liverpool.ac.uk)
英文摘要	Geographical variable distributions often exhibit both macroscale geographic smoothness and microscale discontinuities or local step changes. Nonetheless, accounting for both effects in a unified statistical model is challenging, especially when the data under study involve a multiscale structure and non-Gaussian response variables. This study develops a locally adaptive spatial multilevel logistic model to examine binomial response variables that integrates an innovative locally adaptive spatial econometric model with a multilevel model. It takes into account global spatial autocorrelation, local step changes, and vertical dependence effects arising from the multiscale data structure. Another appealing feature is that the spatial correlation structure, implied by a spatial weights matrix, is learned along with other model parameters via an iterative estimation algorithm, rather than being presumed to be invariant. Bayesian Markov chain Monte Carlo (MCMC) samplers are derived to implement this new spatial multilevel logistic model. A data augmentation approach, drawing on recently devised Polya-gamma distributions, is adopted to reduce computational burdens of calculating binomial likelihoods with a logit link function. The validity of the developed model is evaluated by a set of simulation experiments, before being applied to analyze self-rated health for the elderly in Shijiazhuang, the capital city of Hebei Province, China. Model estimation results highlight a nuanced geography of self-rated health and identify a range of individual- and area-level correlates of health for the elderly. Key Words: geography of health, local spatial modeling, multilevel models, spatial autocorrelation, spatial econometrics.
资助项目	National Natural Science Foundation of China[41822104] ; National Natural Science Foundation of China[41601148] ; Strategic Priority Research Program of the Chinese Academy of Sciences[XDA23100301] ; UK Economic and Social Research Council[ES/P003567/1]
WOS关键词	CONDITIONAL AUTOREGRESSIVE MODELS ; AIR-POLLUTION ; SATISFACTION ; INEQUALITY ; DEPENDENCE ; INFERENCE
WOS研究方向	Geography
语种	英语
出版者	ROUTLEDGE JOURNALS, TAYLOR & FRANCIS LTD
WOS记录号	WOS:000487080400001
资助机构	National Natural Science Foundation of China ; Strategic Priority Research Program of the Chinese Academy of Sciences ; UK Economic and Social Research Council
内容类型	期刊论文
源URL	[http://ir.igsnrr.ac.cn/handle/311030/69545]
专题	中国科学院地理科学与资源研究所
通讯作者	Dong, Guanpeng
作者单位	1.Univ Sheffield, Sch East Asian Studies, Chinese Studies, Sheffield S10 2TN, S Yorkshire, England 2.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Econ Geog, Beijing 100101, Peoples R China 3.Univ Sheffield, Sheffield Methods Inst, Social Stat, Western Bank, Sheffield S10 2TN, S Yorkshire, England 4.Henan Univ, Key Res Inst Yellow River Civilizat & Sustainable, Kaifeng, Peoples R China 5.Henan Univ, Collaborat Innovat Ctr Yellow River Civilizat, Kaifeng, Peoples R China 6.Univ Liverpool, Dept Geog & Planning, Geog Data Sci, Liverpool L69 7ZT, Merseyside, England 7.Beijing Normal Univ, Fac Geog Sci, Beijing Key Lab Remote Sensing Environm & Digital, Beijing, Peoples R China 8.Univ Glasgow, Sch Math & Stat, Stat, Glasgow G12 8SQ, Lanark, Scotland
推荐引用方式 GB/T 7714	Dong, Guanpeng,Ma, Jing,Lee, Duncan,et al. Developing a Locally Adaptive Spatial Multilevel Logistic Model to Analyze Ecological Effects on Health Using Individual Census Records[J]. ANNALS OF THE AMERICAN ASSOCIATION OF GEOGRAPHERS,2019:19.
APA	Dong, Guanpeng,Ma, Jing,Lee, Duncan,Chen, Mingxing,Pryce, Gwilym,&Chen, Yu.(2019).Developing a Locally Adaptive Spatial Multilevel Logistic Model to Analyze Ecological Effects on Health Using Individual Census Records.ANNALS OF THE AMERICAN ASSOCIATION OF GEOGRAPHERS,19.
MLA	Dong, Guanpeng,et al."Developing a Locally Adaptive Spatial Multilevel Logistic Model to Analyze Ecological Effects on Health Using Individual Census Records".ANNALS OF THE AMERICAN ASSOCIATION OF GEOGRAPHERS (2019):19.