The DOI matches its Crossref record.
Assessing the Significance of the Correlation between Two Spatial Processes
Abstract
Modified tests of association based on the correlation coefficient or the covariance between two spatially autocorrelated processes are presented. These tests can be used both for lattice and nonlattice data. They are based on the evaluation of an effective sample size that takes into account the spatial structure. For positively autocorrelated processes, the effective sample size is reduced. A method for evaluating this reduction via an approximation of the variance of the correlation coefficient is developed. The performance of the tests is assessed by Monte Carlo simulations. The method is illustrated by examples from geographical epidemiology.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cited by
F. Dormann, C., M. McPherson, J., B. Araújo, M., Bivand, R., Bolliger, J., Carl, G., G. Davies, R., Hirzel, A., Jetz, W., Daniel Kissling, W., et al. (2007) · Ecography · doi:10.1111/j.2007.0906-7590.05171.x · Cited by 3,433
Spatial Analysis: A Guide for Ecologists
Fortin, M.-J., & Dale, M. R. T. (2005) · doi:10.1017/cbo9780511542039 · Cited by 991
Spatial data analysis: theory and practice
(2004) · Choice Reviews Online · doi:10.5860/choice.41-3486 · Cited by 965
Modifying the t Test for Assessing the Correlation Between Two Spatial Processes
Dutilleul, P., Clifford, P., Richardson, S., & Hemon, D. (1993) · Biometrics · doi:10.2307/2532625 · Cited by 915
Self-citationEffects of incorporating spatial autocorrelation into the analysis of species distribution data
Dormann, C. F. (2007) · Global Ecology and Biogeography · doi:10.1111/j.1466-8238.2006.00279.x · Cited by 658
Metadata
- Authors
- Clifford, P., Richardson, S., & Hemon, D.
- Venue
- Biometrics
- Publisher
- JSTOR
- Published
- 1989-03
- Volume
- 45
- Issue
- 1
- Pages
- 123
- ISSN
- 0006-341X (ISSN-L)
- OpenAlex
- W1976553079
- Cited by
- 637
- References
- 0
- FWCI
- 15.80
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Assessing the Significance of the Correlation between Two Spatial Processes. https://app.cochat.ai/papers/10.2307/2532039
- The paper
- Clifford, P., Richardson, S., & Hemon, D. (1989). Assessing the Significance of the Correlation between Two Spatial Processes. Biometrics. https://doi.org/10.2307/2532039
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
