ArticlePloS one2015
A new methodology of spatial cross-correlation analysis.
Article in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
24 citing papers in PubMed.
- Same-Slide Spatial Multiomics Integration with IN-DEPTH Reveals Tumor Virus-Linked Spatial Reorganization of the Tumor Microenvironment.Cancer discovery · 2026Article
- GALA: a unified landmark-free framework for coarse-to-fine spatial alignment across resolutions and modalities in spatial transcriptomics.Briefings in bioinformatics · 2026Article
- MANTIS: Analytics toolkit for spatial metabolomics with matching spatial transcriptomics data.bioRxiv : the preprint server for biology · 2026Article
- Integrating single-nucleus barcoding with spatial transcriptomics via Stamp-seq to reveal immunotherapy response-enhancing functional modules in NSCLC.Cell discovery · 2026Article
- Using big data to search for possible geographic clustering of Congenital Heart Disease (CHD) across Australia.PLOS digital health · 2026Article
- Variational Characteristics of Vegetation Recovery Period Under Extreme Drought Across Various Land Cover Types in Guizhou Province, China.Ecology and evolution · 2026Article
- Spatial dissimilarity analysis in single-cell transcriptomics.Cell reports methods · 2025Article
- The spatial landscape of glial pathology and T cell response in Parkinson's disease substantia nigra.Nature communications · 2025Article
- The influence of agricultural drought on carbon emissions across the four sub-regions of China.Carbon balance and management · 2025Article
- Mixing individual and collective behaviors to predict out-of-routine mobility.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Vascular access dysfunction incidence among Japanese dialysis patients from NDB Open Data Japan.Scientific reports · 2025Observational
- Spatial distribution characteristics and influencing factors of youth soccer specialty schools in China.Scientific reports · 2024Article
- Defining heritability, plasticity, and transition dynamics of cellular phenotypes in somatic evolution.Nature genetics · 2024Article
- Exploring the urban arbovirus landscape in Rio de Janeiro, Brazil: transmission dynamics and patterns of disease spread.Lancet regional health. Americas · 2024Article
- Article
- Seropositivity of COVID-19 among asymptomatic healthcare workers: A multi-site prospective cohort study from Northern Virginia, United States.Lancet regional health. Americas · 2021Article
- Article
- Measuring geographical disparities in England at the time of COVID-19: results using a composite indicator of population vulnerability.BMJ open · 2020Article
- Use of a Smart Watch for Early Detection of Paroxysmal Atrial Fibrillation: Validation Study.JMIR cardio · 2020Article
- New framework of Getis-Ord's indexes associating spatial autocorrelation with interaction.PloS one · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Spatial correlation modeling comprises both spatial autocorrelation and spatial cross-correlation processes. The spatial autocorrelation theory has been well-developed. It is necessary to advance the method of spatial cross-correlation analysis to supplement the autocorrelation analysis. This paper presents a set of models and analytical procedures for spatial cross-correlation analysis. By analogy with Moran's index newly expressed in a spatial quadratic form, a theoretical framework is derived for geographical cross-correlation modeling. First, two sets of spatial cross-correlation coefficients are defined, including a global spatial cross-correlation coefficient and local spatial cross-correlation coefficients. Second, a pair of scatterplots of spatial cross-correlation is proposed, and the plots can be used to visually reveal the causality behind spatial systems. Based on the global cross-correlation coefficient, Pearson's correlation coefficient can be decomposed into two parts: direct correlation (partial correlation) and indirect correlation (spatial cross-correlation). As an example, the methodology is applied to the relationships between China's urbanization and economic development to illustrate how to model spatial cross-correlation phenomena. This study is an introduction to developing the theory of spatial cross-correlation, and future geographical spatial analysis might benefit from these models and indexes.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.